cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5061/dryad.pzgmsbcgp
title: A new method for quantifying heterochrony in evolutionary lineages

description: The occupation of new environments by evolutionary lineages is frequently
 associated with morphological changes. This co-variation of ecotype and
 phenotype is expected due to the process of natural selection, whereby
 environmental pressures lead to the proliferation of morphological
 variants that are a better fit for the prevailing abiotic conditions. One
 primary mechanism by which phenotypic variants are known to arise is
 through changes in the timing or duration of organismal development
 resulting in alterations to adult morphology, a process known as
 heterochrony. While numerous studies have demonstrated heterochronic
 trends in association with environmental gradients, few have done so
 within a phylogenetic context. Understanding species interrelationships is
 necessary to determine whether morphological change is due to
 heterochronic processes; however, research is hampered by the lack of a
 quantitative metric with which to assess the degree of heterochronic
 traits expressed within and among species. Here I present a new metric for
 quantifying heterochronic change, expressed as a heterochronic weighting,
 and apply it to xiphosuran chelicerates within a phylogenetic context to
 reveal concerted independent heterochronic trends. These trends correlate
 with shifts in environmental occupation from marine to non-marine
 habitats, resulting in a macroevolutionary ratchet. Critically, the
 distribution of heterochronic weightings among species shows evidence of
 being influenced by both historical, phylogenetic processes and external
 ecological pressures. Heterochronic weighting proves to be an effective
 method to quantify heterochronic trends within a phylogenetic framework
 and is readily applicable to any group of organisms that have well-defined
 morphological characteristics, ontogenetic information, and resolved
 internal relationships.
DOI: 10.7272/q63f4mt6
title: Data from: Knowledge, provision of information and barriers to high quality medication abortion provision by pharmacists in Uttar Pradesh, India

description: Background: Almost three quarters of the 16 millions abortions in India
 were medication abortion (MA) purchased outside of facilities. Past
 research has shown low quality of care given to clients seeking MA from
 pharmacists in this setting. Most purchasers of MA from
 pharmacies in India are men, further complicating the pathway to high
 quality information for women taking MA. Developing interventions that can
 improve the information and quality of interactions for
 women obtaining MA through this channel is critical.  Objectives:
 The objective of this study was to measure the impact of an
 informational pamphlet given to pharmacists providing
 medication abortion on provider knowledge and behaviors The study was
 conducted in three districts of Uttar Pradesh India in
 and around Lucknow in 2018.   Study Design: Pre
 intervention surveys were conducted with 283 pharmacists about
 knowledge and practices around MA. Half of the pharmacists were then
 provided with a 2 page informational and pictorial pamphlet. About 6
 months after the baseline survey, pharmacists were again asked to complete
 a similar survey. At the time of recruitment, pharmacists were asked to
 provide consent for a mystery client to visit their shop in the next 6
 months. About 3-4 months after the baseline, 1 of 4 mystery client
 profiles visited 111 pharmacists (both intervention and
 control). Mystery clients presented as 4 profiles (unmarried
 woman, unmarried man, married woman and married man) purchasing MA.
 Findings: Pharmacists had overall low knowledge about
 dosing, timing, side effects and complications for MA. The intervention
 improved pharmacists knowledge of a variety of quality indicators, but did
 not change their self reported practices or behaviors (Mystery client
 data). Pharmacists provided lower quality information to mystery clients
 presenting as women (compared to men), especially young, unmarried
 women.  Conclusions: Intervening to change behaviors among
 pharmacists is challenging and must address both knowledge but also
 behavior change, including stigma and biases. 
description: Mixed methods (pre/post survey and mystery clients)
DOI: 10.5061/dryad.2z34tmphk
title: LAMMPS simulations scripts for the manuscript "A granular-physics-based view of fault friction experiments"

description: Rate- and State-dependent Friction (RSF) equations are commonly used to
 describe the time-dependent frictional response of fault gouge to
 perturbations in sliding velocity. Among the better-known versions are the
 Aging and Slip laws for the evolution of state. Although the Slip law is
 more successful, neither can predict all the robust features of lab data.
 RSF laws are also empirical, and their micromechanical origin is a matter
 of much debate.  Here we use a granular-physics-based model to
 explore the extent to which RSF behavior, as observed in rock and gouge
 friction experiments, can be explained by the response of a granular gouge
 layer with time-independent properties at the contact scale. We examine
 slip histories for which abundant lab data are available, and find that
 the granular model (1) mimics the Slip law for those loading protocols
 where the Slip law accurately models laboratory data (velocity-step and
 slide-hold tests), and (2) deviates from the Slip law under conditions
 where the Slip law fails to match laboratory data (the reslide portions of
 slide-hold-slide tests), in the proper sense to better match those
 data.  The simulations also indicate that state is sometimes
 decoupled from porosity in a way that is inconsistent with traditional
 interpretations of "state" in RSF.  Finally,
 if the "granular temperature" of the gouge is suitably
 normalized by the confining pressure, it produces an estimate of the
 direct velocity effect (the RSF parameter a)  that is consistent
 with our simulations, and in the ballpark of lab data.
description: This repository containts the LAMMPS simulation scripts used for
 running all granular simulations (with quasi-normal and quasi-exponential
 grain size distributions, in files
 "quasi-normal-distribution.zip" and
 "quasi-exponential-distribution.zip", respectively) which their
 results are reported in the manuscript titled "A
 granular-physics-based view of fault friction experiments". The
 repository also includes the instructions for compiling LAMMPS code, and
 for running the simulations (file "lammps_compile_run.pdf"). The
 version of LAMMPS used for running the simulations is "7Aug19"
 and it can be directly downloaded from the LAMMPS older
 versions repository at https://lammps.sandia.gov/tars/.
DOI: 10.5061/dryad.9zw3r22b3
title: Nitrogen isotope composition of amino acids reveals trophic partitioning in two sympatric amphipods

description: According to ecological theory two species cannot occupy the same niche.
 We tested the extent to which two sympatric deposit-feeding amphipods,
 Monoporeia affinis and Pontoporeia femorata, partition trophic resources
 by applying nitrogen isotope analyses (δ15N) of amino acids. We found that
 trophic position (TP), and resynthesis index (∑V; a proxy for degradation
 status of ingested material prior to assimilation by the consumer) differ
 between species. The surface-feeding M. affinis had higher TP and
 intermediate ∑V; both pointing to a large contribution of metazoans in its
 diet. P. femorata, which feeds in the sub-surface layers, had lower TP and
 a bimodal distribution of the ∑V values, supporting previous experimental
 evidence of a larger feeding niche. We also evaluated whether TP and ∑V
 values have consequences for amphipod fecundity and embryo viability and
 found that embryo viability in M. affinis was negatively linked to TP. Our
 results indicate that the amino acid-δ15N data paired with information
 about reproductive status are useful for detecting differences in the
 trophic ecology of sympatric amphipods. Key words: Compound-specific
 stable nitrogen isotope analyses, amino acids, trophic level, resynthesis
 index, reproductive status, Baltic Sea.
description:
DOI: 10.15468/dl.g8jgsr
title: Occurrence Download

description: A dataset containing 45052752 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Netta erythrophthalma, Netta peposaca, Netta rufina, Nettapus auritus, Nettapus coromandelianus, Oxyura ferruginea, Oxyura jamaicensis, Oxyura leucocephala, Oxyura vittata, Plectropterus gambensis, Polysticta stelleri, Pteronetta hartlaubii, Radjah radjah, Sarkidiornis melanotos, Sibirionetta formosa, Spatula clypeata, Spatula cyanoptera, Spatula discors, Spatula hottentota, Spatula platalea, Spatula puna, Spatula rhynchotis, Spatula versicolor, Tadorna cana, Tadorna ferruginea, Tadorna tadornoides, Tadorna variegata, Thalassornis leuconotus, Apteryx australis, Apteryx haastii, Buceros bicornis, Bucorvus abyssinicus, Bucorvus leadbeateri, Bycanistes brevis, Tockus deckeni, Casuarius casuarius, Dromaius novaehollandiae, Actophilornis africanus, Aethia cristatella, Burhinus superciliaris, Charadrius dubius, Chionis albus, Chroicocephalus hartlaubii, Chroicocephalus novaehollandiae, Cursorius cursor, Himantopus himantopus, Himantopus mexicanus, Jacana jacana, Limosa limosa, Pluvianus aegyptius, Scolopax minor, Vanellus armatus, Vanellus chilensis, Vanellus miles, Vanellus spinosus, Anastomus lamelligerus, Ciconia ciconia, Ephippiorhynchus senegalensis, Leptoptilos crumenifer, Leptoptilos crumeniferus, Mycteria ibis, Mycteria leucocephala, Colius striatus, Caloenas nicobarica, Chalcophaps indica, Columba livia)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 45052752 records from 5682 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001911-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/98843wn9yh
title: Dataset of References for the Article on Smart Irrigation with IoT

description: This dataset contains the complete list of references used in the article
“Smart Irrigation in Miniature Roses: A Case Study with IoT and Agriculture 4.0”.
The bibliography includes scientific articles, reports, and sustainability sources.
DOI: 10.17632/98843wn9yh.1
title: Dataset of References for the Article on Smart Irrigation with IoT

description: This dataset contains the complete list of references used in the article
“Smart Irrigation in Miniature Roses: A Case Study with IoT and Agriculture 4.0”.
The bibliography includes scientific articles, reports, and sustainability sources.
DOI: 10.17632/fs2tznkx26.1
title: Replication_SCF_Labor income share_China

description: How supply chain finance policy reduces labor income share of core enterprises ?Evidence from China
DOI: 10.15468/dl.jn9b2a
title: Occurrence Download

description: A dataset containing 17881 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Netherlands",
 "OccurrenceStatus is Present",
 "TaxonKey is Mustela putorius"
 ]
}

 The dataset includes 17881 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008031-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/53y6x98s5d
title: Dataset - SITEC Portuguese Pilot ENPOWER

description: Data used to run a simulation of SITEC for the portuguese pilot
DOI: 10.17632/53y6x98s5d.1
title: Dataset - SITEC Portuguese Pilot ENPOWER

description: Data used to run a simulation of SITEC for the portuguese pilot
DOI: 10.17632/vfxvckrn7h
title: When Green Certification Pays Off: Financial Returns from Environmental Regulation Compliance

description: This study uses data from A-share listed companies in China between 2010 and 2023 and employs a multi-period difference-in-differences model to empirically examine the impact of green factory certification under China’s green manufacturing demonstration program on corporate financial performance. The results show that after obtaining the green factory certification, firms exhibit a significant improvement in financial performance. Mechanism tests reveal that green factory certification incentivizes corporate green innovation, which emphasizes the adoption of new technologies and concepts to achieve efficient resource utilization and effective pollution reduction, thereby generating economic benefits. Additionally, green factory certification enhances firms’ external green image by attracting green investors, leading to market recognition and increased market share, which further improves financial performance. Heterogeneous analyses indicate that the positive effects of green factory certification are stronger for firms with multiple certifications, no environmental violations, stronger public environmental awareness in the region, and firms in heavily polluting industries. Further analysis shows that green factory certification mitigates the negative impact of extreme weather on corporate financial performance. This study provides micro-level empirical evidence on the determinants of corporate financial performance and offers policy implications for the implementation of green manufacturing demonstration projects and voluntary environmental regulation policies.
DOI: 10.17632/vfxvckrn7h.1
title: When Green Certification Pays Off: Financial Returns from Environmental Regulation Compliance

description: This study uses data from A-share listed companies in China between 2010 and 2023 and employs a multi-period difference-in-differences model to empirically examine the impact of green factory certification under China’s green manufacturing demonstration program on corporate financial performance. The results show that after obtaining the green factory certification, firms exhibit a significant improvement in financial performance. Mechanism tests reveal that green factory certification incentivizes corporate green innovation, which emphasizes the adoption of new technologies and concepts to achieve efficient resource utilization and effective pollution reduction, thereby generating economic benefits. Additionally, green factory certification enhances firms’ external green image by attracting green investors, leading to market recognition and increased market share, which further improves financial performance. Heterogeneous analyses indicate that the positive effects of green factory certification are stronger for firms with multiple certifications, no environmental violations, stronger public environmental awareness in the region, and firms in heavily polluting industries. Further analysis shows that green factory certification mitigates the negative impact of extreme weather on corporate financial performance. This study provides micro-level empirical evidence on the determinants of corporate financial performance and offers policy implications for the implementation of green manufacturing demonstration projects and voluntary environmental regulation policies.
DOI: 10.17632/hf2dm2w6yc
title: Kral et al. 2025 (Molecular Cell)_Code

description: This repository contains analysis scripts for Kral et al. (2025) to generate boxplot from Snaptron TCGA data.
DOI: 10.17632/hf2dm2w6yc.2
title: Kral et al. 2025 (Molecular Cell)_Code

description: This repository contains analysis scripts for Kral et al. (2025) to generate boxplot from Snaptron TCGA data.
DOI: 10.17632/crvz87yt6x
title: Replication package for "The Causal Effects of Commodity Shocks"

description: Data and codes that generate the tables and figures of the paper "The Causal Effects of Commodity Shocks"
DOI: 10.17632/crvz87yt6x.1
title: Replication package for "The Causal Effects of Commodity Shocks"

description: Data and codes that generate the tables and figures of the paper "The Causal Effects of Commodity Shocks"
DOI: 10.17632/jps36d9fn9
title: Uterine disorders classification based on symptomic, behaviorial data and ultrasound images

description: The Uterine Disorder Diagnostic Multimodal Dataset (UDDMD-2025) consists of 223 anonymized patient records collected through structured interviews and clinical ultrasound images and reports from the Department of Gynecology, R.S. Unit, Shaheed Tajuddin Ahmad Medical College Hospital, Bangladesh. Data collection took place between May 5–August 7, 2025 (95 days).

Each participant record includes diagnostic parameters extracted from ultrasound and medical reports, along with symptomatic and behavioral indicators gathered in person. All participants provided informed consent and shared their experiences without external influence.

The text dataset is provided as a single .xlsx file (also convertible to .csv), where each row represents one participant and each column corresponds to clinical or behavioral variables. The dataset is publicly accessible via Mendeley Data (DOI: 10.17632/pdzpdgc497.1).

To support multimodal research, the dataset includes a complete set of raw ultrasound images. For every participant in the .xlsx file, a corresponding image directory is provided, named P1, P2, …, P223, allowing direct mapping between tabular data and image evidence. Images were captured using Google Pixel 6 and iPhone 15 Pro devices and are shared in their original, unedited form for flexible preprocessing and analysis.

Ethical clearance was obtained from the Institutional Ethics Committee of Daffodil International University, and permission for clinical data collection was granted by the Assistant Director of Shaheed Tajuddin Ahmad Medical College Hospital.

All diagnostic fields were verified by departmental experts, and ultrasound summaries were manually entered and checked for consistency. The .xlsx file and image folders contain no personally identifiable information, ensuring full anonymization.

Ultrasound summaries were collected immediately after physician consultations, ensuring the reliability of diagnostic information. The combination of raw images and structured text allows robust multimodal applications, including image–text alignment, diagnostic modeling, and cross-modal learning.

This dataset supports research in:
-Predictive modeling of uterine disorders
-Behavioral–clinical correlation analysis
-Machine learning for reproductive health
-Multimodal medical data integration
-Image–text paired training for medical AI

By integrating validated diagnostics, raw ultrasound images, and behavioral indicators, UDDMD-2025 offers a strong foundation for advancing AI-based women’s health research and evidence-driven gynecological analytics.
DOI: 10.17632/jps36d9fn9.1
title: Uterine disorders classification based on symptomic, behaviorial data and ultrasound images

description: The Uterine Disorder Diagnostic Multimodal Dataset (UDDMD-2025) consists of 223 anonymized patient records collected through structured interviews and clinical ultrasound images and reports from the Department of Gynecology, R.S. Unit, Shaheed Tajuddin Ahmad Medical College Hospital, Bangladesh. Data collection took place between May 5–August 7, 2025 (95 days).

Each participant record includes diagnostic parameters extracted from ultrasound and medical reports, along with symptomatic and behavioral indicators gathered in person. All participants provided informed consent and shared their experiences without external influence.

The text dataset is provided as a single .xlsx file (also convertible to .csv), where each row represents one participant and each column corresponds to clinical or behavioral variables. The dataset is publicly accessible via Mendeley Data (DOI: 10.17632/pdzpdgc497.1).

To support multimodal research, the dataset includes a complete set of raw ultrasound images. For every participant in the .xlsx file, a corresponding image directory is provided, named P1, P2, …, P223, allowing direct mapping between tabular data and image evidence. Images were captured using Google Pixel 6 and iPhone 15 Pro devices and are shared in their original, unedited form for flexible preprocessing and analysis.

Ethical clearance was obtained from the Institutional Ethics Committee of Daffodil International University, and permission for clinical data collection was granted by the Assistant Director of Shaheed Tajuddin Ahmad Medical College Hospital.

All diagnostic fields were verified by departmental experts, and ultrasound summaries were manually entered and checked for consistency. The .xlsx file and image folders contain no personally identifiable information, ensuring full anonymization.

Ultrasound summaries were collected immediately after physician consultations, ensuring the reliability of diagnostic information. The combination of raw images and structured text allows robust multimodal applications, including image–text alignment, diagnostic modeling, and cross-modal learning.

This dataset supports research in:
-Predictive modeling of uterine disorders
-Behavioral–clinical correlation analysis
-Machine learning for reproductive health
-Multimodal medical data integration
-Image–text paired training for medical AI

By integrating validated diagnostics, raw ultrasound images, and behavioral indicators, UDDMD-2025 offers a strong foundation for advancing AI-based women’s health research and evidence-driven gynecological analytics.
DOI: 10.17632/2zshchrhjh.2
title: Data and Code for SVEMnet Publication

description: Data and Code for SVEMnet Publication
DOI: 10.17632/v3vwm3jnwh
title: Carbon nanoparticles enhance leaves biomass and potential productivity in Amazonian tree seedlings

description: Data collected at the National Institute of Amazonian Research Campus III in Manaus, Brazil. Study sxperimentation in greenhouse from March 2023 to June 2023. The carbon nanoparticle (CNP) was applied in the substract, once a week during four weeks. Gas exchange measures were taken in the application month. Growth period was carried for other 60 days, and final analyses were performed in June.
DOI: 10.17632/v3vwm3jnwh.2
title: Carbon nanoparticles enhance leaves biomass and potential productivity in Amazonian tree seedlings

description: Data collected at the National Institute of Amazonian Research Campus III in Manaus, Brazil. Study sxperimentation in greenhouse from March 2023 to June 2023. The carbon nanoparticle (CNP) was applied in the substract, once a week during four weeks. Gas exchange measures were taken in the application month. Growth period was carried for other 60 days, and final analyses were performed in June.
DOI: 10.17632/ds3582v368.3
title: Background Values of Trace Metals in the Soil of the Katangan Copperbelt, DR Congo

description: This dataset compiles measurements of trace metals and major elements in soils collected across the Katangan Copperbelt in the Democratic Republic of Congo. The samples were taken from two soil layers (0-25 cm and 25-50 cm) and systematically classified by lithostratigraphic unit. For each sampling point, the dataset includes geographic coordinates, field observations, and concentrations of a broad suite of elements such as As, Co, Cu, Mn, Ni, Pb, Zn. 
Beyond raw concentrations, the dataset provides an interactive map that brings together all results. Users can select the trace metal of interest (e.g. Cu, Co) and the soil horizon (topsoil: 0–25 cm; subsoil: 25–50 cm), access summary statistics (50th and 90th percentiles, mean, standard deviation, coefficient of variation) and display spatial distribution maps for the KCB. The interface allows users to query a point by GPS coordinates and view the PGB values and other statistics of the lithostratigraphic unit in which that point lies. It also supports map export for direct inclusion in reports. Available in French, English and German, this interactive map improves accessibility and uptake by stakeholders.