cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4121/65174478-e69c-400b-ab41-a2f897ceb407.v1
title: Data underlying the study on Reinforcing Prediction of Atomic Energy Level Transitions with Optimized PINN-Bi-LSTM

description: Accurate prediction of atomic energy level transitions is essential for advancements in quantum spectroscopy, quantum device optimization, and atomic dynamics research. Traditional methods often encounter challenges such as high computational cost or limited physical interpretability. To overcome these limitations, the Physics-Informed Bi-LSTM (PINN-Bi-LSTM) model was proposed. This framework integrates Bidirectional Long Short-Term Memory (Bi-LSTM) networks with Physics-Informed Neural Networks (PINNs). The Bi-LSTM component captures temporal patterns in atomic state evolution from time-series data (e.g., spectral emission records), while the PINN component enforces quantum mechanical constraints (e.g., energy conservation, transition probability rules) through a physics-based loss term. The model was validated using both synthetic and experimental datasets and compared against benchmark methods, including ab initio simulations, standalone Bi-LSTMs, and LSTM–ARIMA hybrids. Results demonstrated that the PINN-Bi-LSTM model achieved superior accuracy (0.92), lower mean squared error (0.01), and stronger generalizability to complex systems (e.g., multi-electron atoms, dynamically perturbed states) compared to conventional approaches. Furthermore, the model maintained robust performance in noisy or sparse datasets, attributed to its dual emphasis on data efficiency and physical rigor. This work advances quantum state prediction by unifying temporal modeling capabilities with fundamental physics, offering applications in real-time spectroscopy and quantum device optimization.
DOI: 10.6084/m9.figshare.28943853.v1
title: 100 Years of Penaeid Domestication and Meta-Analysis of Breeding Traits

description: Penaeid shrimp farming plays a pivotal role in ensuring future food security and promoting economic sustainability. Compared with the extensive long history of domestication observed in terrestrial agriculture species, the domestication and selective breeding of penaeids are relatively recent endeavors. Selective breeding aimed at improving production traits holds significant promise for enhancing efficiency and reducing the environmental impact of shrimp farming, thereby contributing to its long-term sustainability. Assessing genotype-by-environment interactions is essential in breeding programs to ensure that improved penaeid shrimp strains perform consistently across different production environments, with genomic selection offers significant advantages over traditional pedigree-based selection in breeding programs. Precision genome editing tools like CRISPR/Cas9 offer significant potential to accelerate genetic gains in penaeid shrimp by enabling rapid introduction of desired genetic changes to enhance production efficiency, improve disease resistance, and reduce environmental impacts. Looking ahead, artificial intelligence is being leveraged to streamline phenotyping and enhance decision-making in shrimp breeding and farming, improving efficiency and accuracy in managing traits and predicting disease outbreaks. Herein, this manuscript provides an overview and update of penaeid shrimp domestication, including the current status for principal farmed species, key historical milestones, targeted breeding traits in selective breeding programs, the advantages of integrating genomic selection for enhancing production traits, and future directions for selective breeding of penaeid shrimp.
DOI: 10.6084/m9.figshare.28417212
title: Worldwide Appraisal of Knowledge Gaps in the Space Usage of Small Pelagic Fish: Highlights Across Stock Uncertainties and Research Priorities

description: Understanding the spatial structure of life cycle components of small pelagic fish (SPF) stocks is key for deciphering population dynamics and ensuring sustainable management. The spatial extent of different life stages and ecologically relevant processes (e.g., reproduction) is temporally dynamic and responds to environmental, genetic, and demographic constraints. Knowledge gaps on within-stock spatial variability of key life cycle processes for SPF worldwide were identified for clupeoid fish (Clupeidae/Engraulidae). From the 3229 Web of Science-indexed articles reviewed, data were systematically extracted from 299. This information was supplemented with another 105 documents and databases from official SPF surveys and stock assessments. Overall, this review compiled information from 111 datasets (77 stocks) involving 17 assessed or commercially relevant species across 19 Large Marine Ecosystems (LMEs) and 38 coastal ecoregions. Only approximately 40% of the stocks used in this study covered the known or presumed stock distribution for at least one life-cycle variable: Adults (feeding area, spawning migration, feeding migration, overwintering migration, spawning area, and presence/biomass), juveniles (presence/biomass, nursery area), and larvae (larval routes). Despite more extensive spatial information from some Eastern Boundary Upwelling Systems (EBUS) and long-managed stocks, some important gaps remain due to information quality, stock identity ambiguity, or spatial data biases. Key information on SPF spatial variability could be extracted from existing surveys, but there were various limitations due to data access and spatiotemporal coverage. The main consequences of the key identified gaps are reviewed, and a series of priority research/monitoring actions are recommended to mitigate these consequences and improve our ability to address spatial variability in SPF stocks.
DOI: 10.6084/m9.figshare.28417212.v1
title: Worldwide Appraisal of Knowledge Gaps in the Space Usage of Small Pelagic Fish: Highlights Across Stock Uncertainties and Research Priorities

description: Understanding the spatial structure of life cycle components of small pelagic fish (SPF) stocks is key for deciphering population dynamics and ensuring sustainable management. The spatial extent of different life stages and ecologically relevant processes (e.g., reproduction) is temporally dynamic and responds to environmental, genetic, and demographic constraints. Knowledge gaps on within-stock spatial variability of key life cycle processes for SPF worldwide were identified for clupeoid fish (Clupeidae/Engraulidae). From the 3229 Web of Science-indexed articles reviewed, data were systematically extracted from 299. This information was supplemented with another 105 documents and databases from official SPF surveys and stock assessments. Overall, this review compiled information from 111 datasets (77 stocks) involving 17 assessed or commercially relevant species across 19 Large Marine Ecosystems (LMEs) and 38 coastal ecoregions. Only approximately 40% of the stocks used in this study covered the known or presumed stock distribution for at least one life-cycle variable: Adults (feeding area, spawning migration, feeding migration, overwintering migration, spawning area, and presence/biomass), juveniles (presence/biomass, nursery area), and larvae (larval routes). Despite more extensive spatial information from some Eastern Boundary Upwelling Systems (EBUS) and long-managed stocks, some important gaps remain due to information quality, stock identity ambiguity, or spatial data biases. Key information on SPF spatial variability could be extracted from existing surveys, but there were various limitations due to data access and spatiotemporal coverage. The main consequences of the key identified gaps are reviewed, and a series of priority research/monitoring actions are recommended to mitigate these consequences and improve our ability to address spatial variability in SPF stocks.
DOI: 10.6084/m9.figshare.28943853
title: 100 Years of Penaeid Domestication and Meta-Analysis of Breeding Traits

description: Penaeid shrimp farming plays a pivotal role in ensuring future food security and promoting economic sustainability. Compared with the extensive long history of domestication observed in terrestrial agriculture species, the domestication and selective breeding of penaeids are relatively recent endeavors. Selective breeding aimed at improving production traits holds significant promise for enhancing efficiency and reducing the environmental impact of shrimp farming, thereby contributing to its long-term sustainability. Assessing genotype-by-environment interactions is essential in breeding programs to ensure that improved penaeid shrimp strains perform consistently across different production environments, with genomic selection offers significant advantages over traditional pedigree-based selection in breeding programs. Precision genome editing tools like CRISPR/Cas9 offer significant potential to accelerate genetic gains in penaeid shrimp by enabling rapid introduction of desired genetic changes to enhance production efficiency, improve disease resistance, and reduce environmental impacts. Looking ahead, artificial intelligence is being leveraged to streamline phenotyping and enhance decision-making in shrimp breeding and farming, improving efficiency and accuracy in managing traits and predicting disease outbreaks. Herein, this manuscript provides an overview and update of penaeid shrimp domestication, including the current status for principal farmed species, key historical milestones, targeted breeding traits in selective breeding programs, the advantages of integrating genomic selection for enhancing production traits, and future directions for selective breeding of penaeid shrimp.
DOI: 10.7910/dvn/bxcpcp
title: The Scientific Logo A Guide for Researchers and Science Communicators

description: This article examines the significance of personal logos in scientific communication, presenting Paolo Fabiani’s logo as a case study. It argues that a scientific logo functions as a visual signature, enhancing authority, attribution, and consistency across publications and digital media. The paper outlines key design principles—including symbol, typography, color psychology, and technical specifications such as pixel dimensions and resolution—and emphasizes the need for scalability and testing in multiple contexts. Finally, it highlights the legal value of documenting and consistently using a logo to establish prior use, ensuring the researcher’s right to maintain its use even if similar logos are later registered.
DOI: 10.6084/m9.figshare.29371990
title: Modeling and interpreting the probability of soil heavy metal contamination in China

description: Heavy metal contamination in soil poses a serious threat to human health. Traditional geostatistical methods struggle to predict contamination over large regions due to the high cost of soil sampling and their limited capacity to analyze complex contamination mechanisms. This study integrates soil contamination data from literature reviews with contamination probability prediction and mechanism analysis using the maximum entropy (Maxent) model. It proposes a predictive framework for assessing soil heavy metal contamination probability (CP) on a large scale. Using China as a case study, the framework predicts the spatial distribution of CP for heavy metals As, Cd, Cr, Cu, Hg, Pb, and Zn in soil, examines influencing factors and city-level CP averages, and provides targeted countermeasures and recommendations. The results indicate that the concentrations of seven heavy metals are strongly associated with regional development levels and mineral resource abundance. High-CP areas are primarily located in developed regions of China, exhibiting planar or clustered distribution patterns. Anthropogenic factors, including population density, GDP (Gross Domestic Product), industrial and mining enterprise density, road density, and land use, are the primary drivers of soil heavy metal contamination. Additionally, industrial upgrading in developed megacities indirectly increases soil heavy metal CP in their satellite cities.
DOI: 10.6084/m9.figshare.29371990.v1
title: Modeling and interpreting the probability of soil heavy metal contamination in China

description: Heavy metal contamination in soil poses a serious threat to human health. Traditional geostatistical methods struggle to predict contamination over large regions due to the high cost of soil sampling and their limited capacity to analyze complex contamination mechanisms. This study integrates soil contamination data from literature reviews with contamination probability prediction and mechanism analysis using the maximum entropy (Maxent) model. It proposes a predictive framework for assessing soil heavy metal contamination probability (CP) on a large scale. Using China as a case study, the framework predicts the spatial distribution of CP for heavy metals As, Cd, Cr, Cu, Hg, Pb, and Zn in soil, examines influencing factors and city-level CP averages, and provides targeted countermeasures and recommendations. The results indicate that the concentrations of seven heavy metals are strongly associated with regional development levels and mineral resource abundance. High-CP areas are primarily located in developed regions of China, exhibiting planar or clustered distribution patterns. Anthropogenic factors, including population density, GDP (Gross Domestic Product), industrial and mining enterprise density, road density, and land use, are the primary drivers of soil heavy metal contamination. Additionally, industrial upgrading in developed megacities indirectly increases soil heavy metal CP in their satellite cities.
DOI: 10.15468/dl.h2vk28
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Suthora alphonsiana",
 "Country is one of (Brunei Darussalam, Indonesia, Philippines, Timor-Leste, Singapore)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028748-250920141307145/datasets/export for details.
DOI: 10.6084/m9.figshare.29688259
title: Characterizing the gendered health burdens of poor water quality in the Global South

description: Safe water is crucial for human health and sustainable development, yet unsafe water disproportionately affects vulnerable populations like women and children. Targeting the Global South, this study combines a systematic literature review and a health risk assessment to examine the gendered health consequences of unsafe water. The review identified 1916 articles in the original search; 428 articles were screened, and 73 articles from 2015 to 2022, onset to midway the UN Sustainable Development Goals era, were included. Nitrate (40%), fluoride (33%), and arsenic (16%) were the most reported water contaminants in the Global South. Fluoride and arsenic were selected for detailed health risk analysis based on the reporting frequency and global data availability. The results show that infants, children, and pregnant women face higher health risks from water contaminants. Women are more susceptible to endocrine-disrupting chemicals and enteric pathogens, while men have slightly higher non-carcinogenic health hazard quotients (HQ) from fluoride and arsenic exposure. Despite low fluoride HQs in most countries, several nations in South America and Asia showed high arsenic HQs, indicating elevated risks of arsenicosis, cancers, and neurological disorders. The study underscores the need to address the gendered impacts of water quality decline, recognizing that water-related issues are not gender-neutral.
DOI: 10.6084/m9.figshare.29688259.v1
title: Characterizing the gendered health burdens of poor water quality in the Global South

description: Safe water is crucial for human health and sustainable development, yet unsafe water disproportionately affects vulnerable populations like women and children. Targeting the Global South, this study combines a systematic literature review and a health risk assessment to examine the gendered health consequences of unsafe water. The review identified 1916 articles in the original search; 428 articles were screened, and 73 articles from 2015 to 2022, onset to midway the UN Sustainable Development Goals era, were included. Nitrate (40%), fluoride (33%), and arsenic (16%) were the most reported water contaminants in the Global South. Fluoride and arsenic were selected for detailed health risk analysis based on the reporting frequency and global data availability. The results show that infants, children, and pregnant women face higher health risks from water contaminants. Women are more susceptible to endocrine-disrupting chemicals and enteric pathogens, while men have slightly higher non-carcinogenic health hazard quotients (HQ) from fluoride and arsenic exposure. Despite low fluoride HQs in most countries, several nations in South America and Asia showed high arsenic HQs, indicating elevated risks of arsenicosis, cancers, and neurological disorders. The study underscores the need to address the gendered impacts of water quality decline, recognizing that water-related issues are not gender-neutral.
DOI: 10.6084/m9.figshare.30231067
title: Genetic and genomic insights into morphological knee defects in Pura Raza Española horses

description: Conformation is a key selection criterion in horse breeding, influencing performance, health and appearance. Knee defects are a common morphological limb defect in horses, and their poorly understood genetics pose a major challenge to breeders. This study aimed to estimate genetic parameters and identify genomic regions associated with knee defects in Pura Raza Español (PRE) horses. Two evaluation approaches were used: continuous variables scored from −4 to 4 for side and front view knee angles (SVKA and FVKA); and multinomial variables on a 5–class scale assessing: buck and calf knee; bench and knock knee. 0 indicated no defect. Genetic analysis and genome-wide association study (GWAS) were performed using weighted single-step genomic BLUP methodology, assessing the knee angle of a total of 58,922 horses, with genotypes available for 4,057 individuals using the Axiom EQUIGENE array. The most prevalent severe defect for the population was knock knee (5.22%), while buck knee and bench knee were the least common (0.12%). Heritability estimates for continuous traits ranged from 0.19 (SVKA) to 0.20 (FVKA), and from 0.13 (bench knee) to 0.38 (knock knee) for independently evaluated traits. GWAS identified 17 genomic regions across seven chromosomes associated with knee defects. Additionally, candidate genes related to musculoskeletal diseases, bone malformations, joint disorders, and cartilage defects were identified. These findings enhance understanding of the genetic basis of knee defects and represent a first step towards genomic selection strategies in PRE horses. Further research is needed to deepen knowledge of conformation-related issues in equine breeding. Analysis of the PRE horse genome has allowed us to locate regions associated with conformation and knee defects. The estimated heritability values indicated a moderate to high genetic influence on the morphological defect of the knee. Seventeen genomic regions were associated with knee conformational defects in horses. Genes related to chondrocytes, synovial joints, bone and cartilage formation, and joint disorders have been found within these regions. This research supports the development of genomic selection strategies to reduce knee defects in PRE horses.
DOI: 10.6084/m9.figshare.30231067.v1
title: Genetic and genomic insights into morphological knee defects in Pura Raza Española horses

description: Conformation is a key selection criterion in horse breeding, influencing performance, health and appearance. Knee defects are a common morphological limb defect in horses, and their poorly understood genetics pose a major challenge to breeders. This study aimed to estimate genetic parameters and identify genomic regions associated with knee defects in Pura Raza Español (PRE) horses. Two evaluation approaches were used: continuous variables scored from −4 to 4 for side and front view knee angles (SVKA and FVKA); and multinomial variables on a 5–class scale assessing: buck and calf knee; bench and knock knee. 0 indicated no defect. Genetic analysis and genome-wide association study (GWAS) were performed using weighted single-step genomic BLUP methodology, assessing the knee angle of a total of 58,922 horses, with genotypes available for 4,057 individuals using the Axiom EQUIGENE array. The most prevalent severe defect for the population was knock knee (5.22%), while buck knee and bench knee were the least common (0.12%). Heritability estimates for continuous traits ranged from 0.19 (SVKA) to 0.20 (FVKA), and from 0.13 (bench knee) to 0.38 (knock knee) for independently evaluated traits. GWAS identified 17 genomic regions across seven chromosomes associated with knee defects. Additionally, candidate genes related to musculoskeletal diseases, bone malformations, joint disorders, and cartilage defects were identified. These findings enhance understanding of the genetic basis of knee defects and represent a first step towards genomic selection strategies in PRE horses. Further research is needed to deepen knowledge of conformation-related issues in equine breeding. Analysis of the PRE horse genome has allowed us to locate regions associated with conformation and knee defects. The estimated heritability values indicated a moderate to high genetic influence on the morphological defect of the knee. Seventeen genomic regions were associated with knee conformational defects in horses. Genes related to chondrocytes, synovial joints, bone and cartilage formation, and joint disorders have been found within these regions. This research supports the development of genomic selection strategies to reduce knee defects in PRE horses.
DOI: 10.15468/dl.jwvy5n
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Cardiocrinum giganteum yunnanense)"
 ]
}

 The dataset includes 41 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028749-250920141307145/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.29821806
title: Associations between meteorological factors and acute myocardial infarction mortality risk in Hefei, China: evidence from a subtropical city

description: Acute myocardial infarction (AMI) remains a leading cause of cardiovascular mortality worldwide. Although meteorological factors have been increasingly linked to health outcomes, evidence of their short-term effects in rapidly urbanizing regions is still limited. Therefore, this study aimed to evaluate the short-term effects of meteorological factors – including daily mean temperature (Tmean), relative humidity (RH), and diurnal temperature range (DTR) – on AMI mortality in Hefei, China, from 2015 to 2020. We applied a generalized additive model (GAM) combined with a distributed lag non-linear model (DLNM) to assess the associations between meteorological factors and AMI mortality, based on daily mortality and meteorological data. The results showed that extremely high Tmean and low DTR significantly increased the AMI mortality risk. Low RH was identified as a risk factor, whereas high RH had a protective effect. Stratified analyses indicated that elderly individuals and women were particularly vulnerable to adverse meteorological conditions. Sensitivity analyses confirmed the results’ robustness. This study provides novel insights into the climate-sensitive risk of AMI mortality amid rapid urbanization and climate change. By identifying key meteorological risk factors and vulnerable subpopulations, our findings offer scientific evidence to support targeted public health interventions and climate-adaptive strategies to reduce AMI-related mortality.