cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15077547
title: Your nose knows what you're looking for!

description: DATA DESCRIPTION

 

Detection Task

The Excel file titled “DetectionTaskResults.xlsx” contains average detection and washing-out times (in seconds) for each participant (coded from S01 to S22) and each target fruit (strawberry, apple, and lemon).

 

Visual Search Task

The Excel file titled “VisualSearchTaskResults.xlsx” contains discrimination performances and average discrimination times for each participant (coded from S01 to S22) and each target fruit (strawberry, apple, and lemon).

This Excel file also includes a table with all the data necessary for error analysis. The table reports:

·      The participant code (from S01 to S22)

·      The trial number where the participant made an error

·      The congruency condition of that trial (NaN = no-odorant, 1 = congruent, 2 = target-incongruent, 3 = distractor-congruent)

·      The odorant delivered (NaN = Neutral, 1 = Strawberry, 2 = Apple, 3 = Lemon)

·      The visual target shown (1 = Strawberry, 2 = Yellow Apple, 3 = Green Apple, 4 = Red Apple, 5 = Lemon)

·      The distractor selected (i.e., the name of a fruit in Italian)

·      The error code (0 = Color & Odorant match; 1 = Color match - Odor mismatch; 2 = Odor match - Color mismatch; 3 = Color & Odorant mismatch)

 

Discrimination Task

The Excel file titled “DiscriminationTaskResults.xlsx” contains discrimination performances and average discrimination times for each participant (coded from S01 to S22) and each target fruit (strawberry, apple, and lemon).
DOI: 10.17632/8hrxgj6ckb.1
title: Self-efficacy of PSTs in Teaching Science in Diverse Classrooms: RIEM

description: This dataset was collected using a standardised and researcher-developed tool: SESSTD (Self-Efficacy Scale for Science Teaching in Diverse Classrooms). This dataset is from 150 Pre-Service Teachers (PSTs) from the Regional Institute of Education (NCERT), Mysuru. This dataset is a part of the researcher's Master of Education Program mandatory Dissertation coursework.
DOI: 10.5281/zenodo.15077507
title: Replication Data for: Infection Risk-Based Application of Plant Resistance Inducers for the Control of Downy and Powdery Mildews in Vineyards

description: The field efficacy of six commercial resistance inducers of chemical and natural origin against downy and powdery mildews were evaluated when applied at designated vine growth stages in a mixture with low doses of copper and sulfur, and only when advised by weather-driven disease models. The disease severity and incidence were evaluated for each season at key growth stages (i.e., the end of flowering, berries pea-sized, veraison, and pre-harvest), and areas under the disease progress curves (AUDPC) were calculated and compared with those of nontreated vines. These risk-based applications resulted in a 41% and 61% reduction of interventions against downy and powdery mildews, respectively, compared to the official advice for integrated pest management in the growing area. Overall, when the disease severity was expressed as AUDPC, we observed higher efficacy of all the resistance inducers for powdery mildew, and of laminarin and cerevisane for downy mildew.
DOI: 10.5281/zenodo.15077508
title: Replication Data for: Infection Risk-Based Application of Plant Resistance Inducers for the Control of Downy and Powdery Mildews in Vineyards

description: The field efficacy of six commercial resistance inducers of chemical and natural origin against downy and powdery mildews were evaluated when applied at designated vine growth stages in a mixture with low doses of copper and sulfur, and only when advised by weather-driven disease models. The disease severity and incidence were evaluated for each season at key growth stages (i.e., the end of flowering, berries pea-sized, veraison, and pre-harvest), and areas under the disease progress curves (AUDPC) were calculated and compared with those of nontreated vines. These risk-based applications resulted in a 41% and 61% reduction of interventions against downy and powdery mildews, respectively, compared to the official advice for integrated pest management in the growing area. Overall, when the disease severity was expressed as AUDPC, we observed higher efficacy of all the resistance inducers for powdery mildew, and of laminarin and cerevisane for downy mildew.
DOI: 10.17632/w6wkp3b6w6
title: A petri net–based framework for smart drug assignment in automated dispensing systems using P-invariants

description: monthly frequency of use + co-use relationship between drugs
DOI: 10.17632/w6wkp3b6w6.1
title: A petri net–based framework for smart drug assignment in automated dispensing systems using P-invariants

description: monthly frequency of use + co-use relationship between drugs
DOI: 10.17632/tjrdk8hmmb
title: LPCAT3-T2DM

description: A dataset exploring the correlation between LPCAT3 and both glycolipid metabolism and type 2 diabetes mellitus
DOI: 10.17632/tjrdk8hmmb.1
title: LPCAT3-T2DM

description: A dataset exploring the correlation between LPCAT3 and both glycolipid metabolism and type 2 diabetes mellitus
DOI: 10.5281/zenodo.15077568
title: Tablas complementarias
DOI: 10.5281/zenodo.15077569
title: Tablas complementarias
DOI: 10.15468/dl.74yg6h
title: Occurrence Download

description: A dataset containing 15261 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Meles meles (Linnaeus, 1758)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON((5.96 45.82, 10.49 45.82, 10.49 47.81, 5.96 47.81, 5.96 45.82))",
 "Year is greater than or equal to 2000",
 "Year is less than or equal to 2010"
 ]
}

 The dataset includes 15261 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025138-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15061504
title: The Coralscapes Dataset: Semantic Scene Understanding in Coral Reefs

description: The Coralscapes dataset is the first general-purpose dense semantic segmentation dataset for coral reefs. Similar in scope and with the same structure as the widely used Cityscapes dataset for urban scene understanding, Coralscapes allows for the benchmarking of semantic segmentation models in a new challenging domain. The Coralscapes dataset spans 2075 images at 1024×2048px resolution gathered from 35 dive sites in 5 countries in the Red Sea, labeled in a consistent and speculation-free manner containing 174k polygons over 39 benthic classes.

This repository provides a collection of scripts and instructions for working with the Coralscapes dataset. It includes the full codebase necessary for training and evaluating models on this dataset, allowing to reproduce the results in the paper. Additionally, it contains scripts and step-by-step guidance on how to use the trained models for inference and how to fine-tune the models to external datasets.



Dataset Structure


The dataset structure of the Coralscapes dataset follows the structure of the Cityscapes dataset:



{root}/{type}/{split}/{site}/{site}_{seq:0>6}_{frame:0>6}_{type}{ext}



The meaning of the individual elements is:



root the root folder of the Coralscapes dataset.

type the type/modality of data, gtFine for fine ground truth, leftImg8bit for left 8-bit images, leftImg8bit_1080p (gtFine_1080p) for the images (ground truth) in 1080p resolution, leftImg8bit_videoframes for the 19 preceding and 10 trailing video frames.

split the split, i.e. train/val/test. Note that not all kinds of data exist for all splits. Thus, do not be surprised to occasionally find empty folders.

site ID of the site in which this part of the dataset was recorded.

seq the sequence number using 6 digits.

frame the frame number using 6 digits.

ext .png


 

File Structure

The files provided in the Zenodo repository are the following:



coralscapes.7z contains the Coralscapes dataset which includes the 2075 images and corresponding ground truth semantic segmentation masks at 1024x2048px resolution.

coralscapes_1080p.7z contains the Coralscapes images and masks in their native 1080x1920px resolution.

model_checkpoints.7z contains the checkpoints of the semantic segmentation models that have been fine-tuned on the Coralscapes dataset. This includes the following models: SegFormer (with a B2 and B5 backbone, trained with and without LoRA), DPT (with a DINOv2-Base and DINOv2-Giant backbone, trained with and without LoRA), a Linear segmentation model with a DINOv2-Base backbone, a UNet++ with a ResNet50 backbone and DeepLabV3+ with a ResNet50 backbone.   

coralscapes_videoframes.7z contains the the 19 preceding and 10 trailing video frames of each image in the Coralscapes dataset.
DOI: 10.5281/zenodo.15061505
title: The Coralscapes Dataset: Semantic Scene Understanding in Coral Reefs

description: The Coralscapes dataset is the first general-purpose dense semantic segmentation dataset for coral reefs. Similar in scope and with the same structure as the widely used Cityscapes dataset for urban scene understanding, Coralscapes allows for the benchmarking of semantic segmentation models in a new challenging domain. The Coralscapes dataset spans 2075 images at 1024×2048px resolution gathered from 35 dive sites in 5 countries in the Red Sea, labeled in a consistent and speculation-free manner containing 174k polygons over 39 benthic classes.

This repository provides a collection of scripts and instructions for working with the Coralscapes dataset. It includes the full codebase necessary for training and evaluating models on this dataset, allowing to reproduce the results in the paper. Additionally, it contains scripts and step-by-step guidance on how to use the trained models for inference and how to fine-tune the models to external datasets.



Dataset Structure


The dataset structure of the Coralscapes dataset follows the structure of the Cityscapes dataset:



{root}/{type}/{split}/{site}/{site}_{seq:0>6}_{frame:0>6}_{type}{ext}



The meaning of the individual elements is:



root the root folder of the Coralscapes dataset.

type the type/modality of data, gtFine for fine ground truth, leftImg8bit for left 8-bit images, leftImg8bit_1080p (gtFine_1080p) for the images (ground truth) in 1080p resolution, leftImg8bit_videoframes for the 19 preceding and 10 trailing video frames.

split the split, i.e. train/val/test. Note that not all kinds of data exist for all splits. Thus, do not be surprised to occasionally find empty folders.

site ID of the site in which this part of the dataset was recorded.

seq the sequence number using 6 digits.

frame the frame number using 6 digits.

ext .png


 

File Structure

The files provided in the Zenodo repository are the following:



coralscapes.7z contains the Coralscapes dataset which includes the 2075 images and corresponding ground truth semantic segmentation masks at 1024x2048px resolution.

coralscapes_1080p.7z contains the Coralscapes images and masks in their native 1080x1920px resolution.

model_checkpoints.7z contains the checkpoints of the semantic segmentation models that have been fine-tuned on the Coralscapes dataset. This includes the following models: SegFormer (with a B2 and B5 backbone, trained with and without LoRA), DPT (with a DINOv2-Base and DINOv2-Giant backbone, trained with and without LoRA), a Linear segmentation model with a DINOv2-Base backbone, a UNet++ with a ResNet50 backbone and DeepLabV3+ with a ResNet50 backbone.   

coralscapes_videoframes.7z contains the the 19 preceding and 10 trailing video frames of each image in the Coralscapes dataset.
DOI: 10.5281/zenodo.15077541
title: Supporting data for [Characteristics of Super Atmospheric Rivers Associated with Explosive Extratropical Cyclones over the Northern Pacific Ocean]

description: This dataset contains composited fileds data of 118 ARs/EECs in the article "Characteristics of Super Atmospheric Rivers Associated with Explosive Extratropical Cyclones over the Northern Pacific Ocean".
DOI: 10.5281/zenodo.15077542
title: Supporting data for [Characteristics of Super Atmospheric Rivers Associated with Explosive Extratropical Cyclones over the Northern Pacific Ocean]

description: This dataset contains composited fileds data of 118 ARs/EECs in the article "Characteristics of Super Atmospheric Rivers Associated with Explosive Extratropical Cyclones over the Northern Pacific Ocean".
DOI: 10.15468/dl.p3f2r7
title: Occurrence Download

description: A dataset containing 263 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Acacia rigidula Benth.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 263 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025141-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5e3aet
title: Occurrence Download

description: A dataset containing 2295 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is South America",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ateles paniscus (Linnaeus, 1758)"
 ]
}

 The dataset includes 2295 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025142-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15074074
title: CAM-NET inference model outputs and plotting code

description: CAM-NET inference model outputs and plotting code

This Zenodo directory contains the CAM-NET inference model outputs and corresponding target values for both large and small scales. The data is in .npy format, which can be efficiently read by Python.

Each dataset has dimensions of (20, 116, 192, 288), representing the axes of time, channels, latitude, and longitude, respectively.

The plotting script FigPlotting.py compares the inference outputs with the target values, visualizes their differences, and evaluates the performance of the CAM-NET model.
DOI: 10.5281/zenodo.15074075
title: CAM-NET inference model outputs and plotting code

description: CAM-NET inference model outputs and plotting code

This Zenodo directory contains the CAM-NET inference model outputs and corresponding target values for both large and small scales. The data is in .npy format, which can be efficiently read by Python.

Each dataset has dimensions of (20, 116, 192, 288), representing the axes of time, channels, latitude, and longitude, respectively.

The plotting script FigPlotting.py compares the inference outputs with the target values, visualizes their differences, and evaluates the performance of the CAM-NET model.
DOI: 10.5281/zenodo.15077592
title: Replication Data for: Pre-infection efficacy of resistance inducers against grapevine powdery mildew

description: The effects of four commercial plant resistance inducers, of natural and microbial origin, on the development of powdery mildew (PM) on grapevine leaves over a 3-year period. Disease and sporulation severity were evaluated following the artificial inoculation of treated leaves with Erysiphe necator conidia at 1, 3, 7 and 12 days after treatment (DAT). Laminarin (LAM) and cos-oga (COS) were the most effective in reducing both disease (57.1% and 49.5%, respectively) and sporulation (85.3% and 90.2%, respectively) severity; the reduction in PM severity provided by cerevisane (CER) was lower (27%), and that of Pythium oligandrum (PYT) was intermediate (44.9%). LAM was effective from 1 DAT, while COS and PYT were more effective when E. necator was inoculated at 7 to 12 DAT. The effect of resistance inducers on the sporulation of E. necator colonies also suggests a broader and longer effect on PM epidemics.
DOI: 10.5281/zenodo.15077593
title: Replication Data for: Pre-infection efficacy of resistance inducers against grapevine powdery mildew

description: The effects of four commercial plant resistance inducers, of natural and microbial origin, on the development of powdery mildew (PM) on grapevine leaves over a 3-year period. Disease and sporulation severity were evaluated following the artificial inoculation of treated leaves with Erysiphe necator conidia at 1, 3, 7 and 12 days after treatment (DAT). Laminarin (LAM) and cos-oga (COS) were the most effective in reducing both disease (57.1% and 49.5%, respectively) and sporulation (85.3% and 90.2%, respectively) severity; the reduction in PM severity provided by cerevisane (CER) was lower (27%), and that of Pythium oligandrum (PYT) was intermediate (44.9%). LAM was effective from 1 DAT, while COS and PYT were more effective when E. necator was inoculated at 7 to 12 DAT. The effect of resistance inducers on the sporulation of E. necator colonies also suggests a broader and longer effect on PM epidemics.
DOI: 10.6084/m9.figshare.28652051
title: Palaeoceanographic changes during the late Albian-early Turonian in the Sergipe Alagoas Basin

description: The file contains six worksheets: (1) the “XRF raw data” worksheet provides the X-Ray Fluorescence data obtained in samples from the Sergipe-Alagoas Basin. Analyses were performed using a Rigaku Supermini 200 Wavelength Dispersive XRF sequential spectrometer and the ZSX software by Rigaku. Results are displayed in counts per second. Only the data discussed in the paper “Palaeoceanographic changes during the late Albian-early Turonian in the Sergipe-Alagoas Basin (Northeast of Brazil) and their link with global events” are reported. ND: not determined; (2) the “XRF normalized” worksheet presents the elemental data as normalized to the sum of all elements measured in a sample and as log ratios. ND: not determined; (3) the “Magnetic data” worksheet contains Magnetic Susceptibility (MS) values measured at 976 Hz (Frequency 1) using a MFK1-FA Kappabridge (Advanced Geophysical Instruments Company, AGICO), and paleomagnetic data obtained with a 2G Enterprises 755-4K Long Core Squid magnetometer and a pulser. They include the Saturation of Isothermal Remanent Magnetization (SIRM), Backfield Isothermal Remanent Magnetization (BIRM), and S-ratio. MS/Fe values were obtained after normalizing both MS (m<sup>3</sup>/Kg) and Fe/sum data to the mean equals zero and standard deviation equals one (i.e., zero-mean normalization); (4) the “Age model” worksheet contains the ln(K/Al) data linearly interpolated for an average sampling space of 3 m, linearly detrended, and filtered for frequencies from 0.04 to 0.005 cycles/m. The worksheet also includes the tie points obtained by tuning the filtered ln(K/Al) data with the astronomical solution from Laskar (2020) and the sedimentation rates; (5) cross-correlation between ln(K/Al) and ln(Ca/Fe) data; (6) ln(Ca/Fe) data interpolated for an average sampling space of 3 m.
DOI: 10.15468/dl.eceexd
title: Occurrence Download

description: A dataset containing 507 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Acacia riparia Bertero, Acacia riparia Bertero ex Spreng., Acacia riparia Kunth)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 507 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025144-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13145/bacdive120409.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0112045.10fu
title: SH0112045.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive120409.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive120410.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0112046.10fu
title: SH0112046.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive120410.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive120411.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0112047.10fu
title: SH0112047.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.