cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/jfcz7gh7yc.1
title: MOYA FISH

description: ### Data Description: Good and Bad Classification of Moya Fish (Mola Mola)

*Data Collection Overview:*
The dataset consists of over 500 images of Moya fish (Mola Mola), captured for the purpose of classifying them into two categories: "Good" and "Bad." The images were taken using a Redmi 9 Power mobile camera, ensuring a consistent image quality. All images were captured against a black background in daylight conditions, which provides uniform lighting and minimizes distractions, enhancing the focus on the fish's features.

*Camera and Environmental Conditions:*
- *Camera Used:* Redmi 9 Power mobile camera.
- *Resolution:* The images are expected to be of high resolution, typically around 48 MP, given the camera specifications.
- *Background:* The black background ensures high contrast between the fish and its surroundings, making it easier to distinguish and analyze the features of the fish.
- *Lighting:* Daylight conditions were used to illuminate the fish naturally, avoiding harsh shadows or artificial lighting effects that could alter the fish's appearance.

*Dataset Composition:*
- *Total Images:* The dataset includes more than 500 images, with an approximately equal distribution between "Good" and "Bad" classifications.
- *Good Moya Fish:* These are images where the fish are healthy, intact, and exhibit ideal physical characteristics such as a smooth body surface, symmetrical fins, and clear eyes.
- *Bad Moya Fish:* These images capture fish that may have deformities, damage, disease, or any physical imperfections that deviate from the ideal standards. This could include discoloration, missing parts, abnormal growths, or signs of infection.

*Image Attributes:*
- *Format:* The images are likely in a standard format such as JPEG or PNG, commonly supported by mobile cameras.
- *Color Space:* The images are captured in color (RGB), which is crucial for distinguishing subtle differences in fish coloration that might indicate good or bad quality.
- *Orientation:* Images are expected to be consistently oriented to present the fish in a similar perspective across the dataset, facilitating easier comparison and classification.

*Use Case and Applications:*
This dataset is valuable for developing machine learning models that can automatically classify Moya fish into "Good" or "Bad" categories. Such models can be used in aquaculture, fisheries management, and quality control processes to ensure only the highest quality fish are selected for further processing or sale.

*Challenges:*
- *Variability in Fish Appearance:* Despite the controlled conditions, natural variability in the fish’s appearance may pose challenges in classification, necessitating a robust model that can handle such variations.

This dataset serves as a comprehensive resource for developing, testing, and validating classification algorithms aimed at assessing the quality of Moya fish, contributing to advancements in automated fish quality assessment systems.
DOI: 10.17632/42wwx5559b.2
title: IPRP and CEE

description: This document is for the paper "Does intellectual property rights protection matter for low-carbon transition? The role of institutional incentives".
DOI: 10.17632/zr2ddj7scw.1
title: From Policy to Practice: The Role of National Policy Instruments and Social Barriers in UK Energy Efficiency Adoption in households

description: Original survey data of a representative sample of households in the UK (2022) and codes for replication of paper - From Policy to Practice: The Role of National Policy Instruments and Social Barriers in UK Energy Efficiency Adoption in households
DOI: 10.17632/3bxh6ps5x7.1
title: Academic and motivational data of patentees from brazilian public universities

description: The dataset includes academic, behavioral, and motivational information about researchers affiliated with Brazilian public universities. Data were gathered through an online survey using a questionnaire and were further enriched with professional and academic details from public databases. The sample consists of prolific patentees from these institutions.
DOI: 10.6084/m9.figshare.21566019.v1
title: Bandopadhyay_N_amendment_Dataset

description: This file includes raw datasets used to prepare figures and tables for manuscript titled "Organic and inorganic nitrogen amendments suppress decomposition of biodegradable plastic mulch films" to be submitted by Bandopadhyay et al. to the journal SOIL by EGU.
<br>
DOI: 10.15468/dl.xgkkjp
title: Occurrence Download

description: A dataset containing 6153 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Acacia irrorata Sieber ex Spreng."
 ]
}

 The dataset includes 6153 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0105379-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2qceh6
title: Occurrence Download

description: A dataset listing the 4743 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-73.16456 -37.2933,-72.14939 -37.2933,-72.14939 -36.5246,-73.16456 -36.5246,-73.16456 -37.2933))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset's 4743 records were derived from 308 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0105279-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/57rhkyn7fh.1
title: Effects of Ozone Pretreatment and Caffeic Acid Modification on the Structure and Properties of Banana Starch

description: The following CSV file is the original data for the article.
DOI: 10.25574/01101
title: Chandra X-ray Observatory ObsId 01101
DOI: 10.25574/01167
title: Chandra X-ray Observatory ObsId 01167
DOI: 10.25574/01244
title: Chandra X-ray Observatory ObsId 01244
DOI: 10.25574/01246
title: Chandra X-ray Observatory ObsId 01246
DOI: 10.15468/dl.vmxhkh
title: Occurrence Download

description: A dataset listing the 3 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is Chile",
 "TaxonKey is Myocastor coypus (Molina, 1782)"
 ]
}

 The dataset's 3 records were derived from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0105297-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11175125
title: A proteome-wide quantitative platform for nanoscale spatially resolved extraction of membrane proteins into native nanodiscs

description: EM Quantitation:

Raw data gathered from EM images taken to determine nanodisc population size distribution.

 

NNB TGN46 analysis:

Data analysis of the Native Nanobleach experiments of TGN46 in native nanodiscs to determine population distribution of oligomeric organizations.

 

Polymer conditions:

Physiochemical characteristic and extraction conditions for all polymers in the library both commercially available and in-house.

 

Protein groups polymer screen original file:

Original output of MaxQuant data processing of polymer screen data.

 

Organelle matching:

Code used for mathcing proteins identified in the proteomics output to organelle or residence for all organellar annotations.

 

Polymer code:

Code used to process and normalize the MaxQuant output and calulate extraction efficiency across all detected proteins.
DOI: 10.5281/zenodo.11175124
title: A proteome-wide quantitative platform for nanoscale spatially resolved extraction of membrane proteins into native nanodiscs

description: EM Quantitation:

Raw data gathered from EM images taken to determine nanodisc population size distribution.

 

NNB TGN46 analysis:

Data analysis of the Native Nanobleach experiments of TGN46 in native nanodiscs to determine population distribution of oligomeric organizations.

 

Polymer conditions:

Physiochemical characteristic and extraction conditions for all polymers in the library both commercially available and in-house.

 

Protein groups polymer screen original file:

Original output of MaxQuant data processing of polymer screen data.

 

Organelle matching:

Code used for mathcing proteins identified in the proteomics output to organelle or residence for all organellar annotations.

 

Polymer code:

Code used to process and normalize the MaxQuant output and calulate extraction efficiency across all detected proteins.

 

MAP Library Details:

Graphic and table explaining chemical details of all polymer used in the screen, both commerically available and in-house synthesized.

 

NNB TGN46:

Raw scope files for the TIRF microscopy single molecule step photobleaching experiment with TGN46.

 

Organellar Breakdown Database:

Proteins detected in the polymer screen through proteomics experiments stratified into organelle of residence.

 

Human Proteome FASTA:

The FASTA file used for proteome searching in processing the proteomics data to build the screening database.

 

Hand Curated Organellar Proteomes:

Organellar proteomes used for organellar sorting and identification of proteins detected in the screen.

 

Polymer SEC Superdex75:

Size exculsion chromatography traces for chloroSMA series of polymers. Was used to characterize length and population polydispersity.

 

Negative Stain Raw:

RAW TEM scope images of purified synaptophysin-vamp2 containing nanodiscs. Populatoin size distribution was determined.

 

FSEC Polymer CS80:

Fluoresence size exclusion chromatogram for purified synaptophysin-vamp2 containing nanodiscs to ensure population homogeneity and purity.

NMR Raw data:

NMR raw files for characterizing the in-house synthesized Chloro-SMA series and AASTY series.
DOI: 10.5281/zenodo.13380404
title: A proteome-wide quantitative platform for nanoscale spatially resolved extraction of membrane proteins into native nanodiscs

description: EM Quantitation:

Raw data gathered from EM images taken to determine nanodisc population size distribution.

 

NNB TGN46 analysis:

Data analysis of the Native Nanobleach experiments of TGN46 in native nanodiscs to determine population distribution of oligomeric organizations.

 

Polymer conditions:

Physiochemical characteristic and extraction conditions for all polymers in the library both commercially available and in-house.

 

Protein groups polymer screen original file:

Original output of MaxQuant data processing of polymer screen data.

 

Organelle matching:

Code used for mathcing proteins identified in the proteomics output to organelle or residence for all organellar annotations.

 

Polymer code:

Code used to process and normalize the MaxQuant output and calulate extraction efficiency across all detected proteins.

 

MAP Library Details:

Graphic and table explaining chemical details of all polymer used in the screen, both commerically available and in-house synthesized.

 

NNB TGN46:

Raw scope files for the TIRF microscopy single molecule step photobleaching experiment with TGN46.

 

Organellar Breakdown Database:

Proteins detected in the polymer screen through proteomics experiments stratified into organelle of residence.

 

Human Proteome FASTA:

The FASTA file used for proteome searching in processing the proteomics data to build the screening database.

 

Hand Curated Organellar Proteomes:

Organellar proteomes used for organellar sorting and identification of proteins detected in the screen.

 

Polymer SEC Superdex75:

Size exculsion chromatography traces for chloroSMA series of polymers. Was used to characterize length and population polydispersity.

 

Negative Stain Raw:

RAW TEM scope images of purified synaptophysin-vamp2 containing nanodiscs. Populatoin size distribution was determined.

 

FSEC Polymer CS80:

Fluoresence size exclusion chromatogram for purified synaptophysin-vamp2 containing nanodiscs to ensure population homogeneity and purity.

NMR Raw data:

NMR raw files for characterizing the in-house synthesized Chloro-SMA series and AASTY series.
DOI: 10.15468/dl.6xnerf
title: Occurrence Download

description: A dataset containing 236 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Epidendrum zipaquiranum Schltr."
 ]
}

 The dataset includes 236 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0105380-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18430/m38ab1
title: X-ray diffraction data for the crystal structure of the PulL-PulM C-terminal domain heterocomplex (8AB1)
DOI: 10.15468/dl.mxdqr4
title: Occurrence Download

description: A dataset containing 98202 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 {
 "and" : [
 "BasisOfRecord is one of (Material sample, Specimen)",
 "Country is one of (Colombia)",
 "TaxonKey is one of (Mammalia)"
 ]
 }
 ]
}

 The dataset includes 98202 records from 241 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0105381-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w4qb7b
title: Occurrence Download

description: A dataset containing 4489 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Peucaea humeralis (Cabanis, 1851)"
 ]
}

 The dataset includes 4489 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0105383-240626123714530/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.21631904
title: Forest disturbance and recovery_1988_2021

description: A long time series Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr, LT) algorithm and Google Earth Engine (GEE) is used to monitor the time, duration, and magnitude dynamics of forest disturbance and recovery (1987–2021) in Heyuan City, northeastern Guangdong Province, southern China. <br>
DOI: 10.25452/figshare.plus.21632564
title: "Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq" Replogle et al. 2022 - commonly requested supplemental files

description: Commonly requested supplemental files supporting the publication: Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq, Replogle, Joseph M. et al. Cell, Volume 185, Issue 14, 2559 - 2575.e28 https://doi.org/10.1016/j.cell.2022.05.013: <br> 1) All Anderson-Darling p-values for differential expression analysis <br> 2) Embedding coordinates for Figure 2D <br> 3) Downloadable interactive scatter plot of Fig. 2D <br> 4) Z-normalized expression data used to make Figs. 2 and 4, annotated with the cluster identities from Supplementary Table 3 <br> See related datasets at: https://doi.org/10.25452/figshare.plus.20029387 https://doi.org/10.25452/figshare.plus.20127869 https://doi.org/10.25452/figshare.plus.20022944
DOI: 10.25800/qhhp-sf77
title: DSA-110 Data for Candidate Fast Radio Burst 221025aanu

description: Data associated with DSA-110 candidate transient. Zipped file contains (1) a filterbank file with burst dynamic spectrum and (2) a FITS file with localization region. Second file is a png image showing summary views of data used to identify the candidate.
DOI: 10.5281/zenodo.5663917
title: Quasilinear Model of Jovian Whistler Mode Emission

description: This is the supporting data set for the paper by the same title published in AGU JGR Space Physics, 10.1029/2021JA029930 <strong>Key Points:</strong> Quasilinear model of whistler instability excited by the loss-cone electron distribution is formulated. The theoretical result compares reasonably well against Juno observation. This shows that the quasilinear theory is a useful tool for interpreting Jovian plasma wave emissions and radiations. <strong>Abstract</strong> The whistler mode chorus emissions are pervasively detected by the Juno satellite in Jupiter’s magnetospheric environment. The present paper pays particular attention to a sample observation made by the Juno on November 3, 2019, where typical whistler mode chorus waves are measured. The emission is characterized by a broad range of wave frequencies from below f<sub>ce</sub> /2, where f<sub>ce</sub> denotes the local electron cyclotron frequency,down to the lower-hybrid frequency, with a gradually downshifting frequency over time. The excitation appears to coincide with the detection of a “butterfly” pitch-angle distribution and the expected loss-cone feature associated with the energetic electrons. These anisotropic features, especially the butterfly pitch-angle distribution, gradually disappear as the waves are excited and the electron phase space distribution becomes isotropic. The present paper models these characteristics by means of quasilinear kinetic theory of the whistler instability driven by a loss-cone electron distribution function with a narrow loss-cone angle, which is to be expected from low-latitude regions of the Jovian magnetosphere. It is shown that the theoretically constructed dynamic wave spectrum is consistent with the observation made on Nov. 3, 2019. The present finding demonstrates that the quasilinear theory can be a powerful theoretical tool for interpreting various Jovian plasma wave emissions, which includes the whistler waves, but also other wave modes.
DOI: 10.5281/zenodo.5663916
title: Quasilinear Model of Jovian Whistler Mode Emission

description: This is the supporting data set for the paper by the same title published in AGU JGR Space Physics, 10.1029/2021JA029930 <strong>Key Points:</strong> Quasilinear model of whistler instability excited by the loss-cone electron distribution is formulated. The theoretical result compares reasonably well against Juno observation. This shows that the quasilinear theory is a useful tool for interpreting Jovian plasma wave emissions and radiations. <strong>Abstract</strong> The whistler mode chorus emissions are pervasively detected by the Juno satellite in Jupiter’s magnetospheric environment. The present paper pays particular attention to a sample observation made by the Juno on November 3, 2019, where typical whistler mode chorus waves are measured. The emission is characterized by a broad range of wave frequencies from below f<sub>ce</sub> /2, where f<sub>ce</sub> denotes the local electron cyclotron frequency,down to the lower-hybrid frequency, with a gradually downshifting frequency over time. The excitation appears to coincide with the detection of a “butterfly” pitch-angle distribution and the expected loss-cone feature associated with the energetic electrons. These anisotropic features, especially the butterfly pitch-angle distribution, gradually disappear as the waves are excited and the electron phase space distribution becomes isotropic. The present paper models these characteristics by means of quasilinear kinetic theory of the whistler instability driven by a loss-cone electron distribution function with a narrow loss-cone angle, which is to be expected from low-latitude regions of the Jovian magnetosphere. It is shown that the theoretically constructed dynamic wave spectrum is consistent with the observation made on Nov. 3, 2019. The present finding demonstrates that the quasilinear theory can be a powerful theoretical tool for interpreting various Jovian plasma wave emissions, which includes the whistler waves, but also other wave modes.
DOI: 10.5517/ccdc.csd.cc28qz44
title: CCDC 2107446: Experimental Crystal Structure Determination

description: Related Article: Valentin Vaillant-Coindard, Benjamin Théron, Gaël Printz, Florian Chotard, Cédric Balan, Yoann Rousselin, Philippe Richard, Iogann Tolbatov, Paul Fleurat-Lessard, Ewen Bodio, Raluca Malacea-Kabbara, Jérôme Bayardon, Samuel Dagorne, Pierre Le Gendre|2022|Organometallics|41|2920|doi:10.1021/acs.organomet.2c00343
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28qz55
title: CCDC 2107447: Experimental Crystal Structure Determination

description: Related Article: Valentin Vaillant-Coindard, Benjamin Théron, Gaël Printz, Florian Chotard, Cédric Balan, Yoann Rousselin, Philippe Richard, Iogann Tolbatov, Paul Fleurat-Lessard, Ewen Bodio, Raluca Malacea-Kabbara, Jérôme Bayardon, Samuel Dagorne, Pierre Le Gendre|2022|Organometallics|41|2920|doi:10.1021/acs.organomet.2c00343
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28qz66
title: CCDC 2107448: Experimental Crystal Structure Determination

description: Related Article: Valentin Vaillant-Coindard, Benjamin Théron, Gaël Printz, Florian Chotard, Cédric Balan, Yoann Rousselin, Philippe Richard, Iogann Tolbatov, Paul Fleurat-Lessard, Ewen Bodio, Raluca Malacea-Kabbara, Jérôme Bayardon, Samuel Dagorne, Pierre Le Gendre|2022|Organometallics|41|2920|doi:10.1021/acs.organomet.2c00343
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28qz77
title: CCDC 2107449: Experimental Crystal Structure Determination

description: Related Article: Valentin Vaillant-Coindard, Benjamin Théron, Gaël Printz, Florian Chotard, Cédric Balan, Yoann Rousselin, Philippe Richard, Iogann Tolbatov, Paul Fleurat-Lessard, Ewen Bodio, Raluca Malacea-Kabbara, Jérôme Bayardon, Samuel Dagorne, Pierre Le Gendre|2022|Organometallics|41|2920|doi:10.1021/acs.organomet.2c00343
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28qz88
title: CCDC 2107450: Experimental Crystal Structure Determination

description: Related Article: Valentin Vaillant-Coindard, Benjamin Théron, Gaël Printz, Florian Chotard, Cédric Balan, Yoann Rousselin, Philippe Richard, Iogann Tolbatov, Paul Fleurat-Lessard, Ewen Bodio, Raluca Malacea-Kabbara, Jérôme Bayardon, Samuel Dagorne, Pierre Le Gendre|2022|Organometallics|41|2920|doi:10.1021/acs.organomet.2c00343
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.