cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/sytpg5h225.1
title: How Succesful Is AI And Non-AI Advertising? An Example of Meta Ads for Fashion Product Campaigns on Social Media Platforms

description: Today, the digital world is becoming more advanced. Many people need AI (Artificial Intelligence) to help them run their businesses. This study aims to analyze the effectiveness of digital advertising using Artificial Intelligence-based content compared to non-AI content in Meta Ads campaigns for Women's fashion products. In this experiment, two sets of ad campaigns ran in parallel on the Facebook and Instagram platforms for seven days, each using visual content created without AI and using AI. The metrics analyzed include impressions, cost-per-click (CPC), cost-per-result (CPR), cost-per- message conversion, click-through rate (CTR), and total messages received through WhatsApp Business as a form of conversion. Results show that AI-driven ads excel in generating the number of messages (91 messages) compared to non- AI content (82 messages)
DOI: 10.17632/zgxfpkpy2f.1
title: Environmental Regulation, Green Innovation, and Productivity: Crowding-Out or Reallocation?

description: Replication package for the paper in Economic Modelling.
DOI: 10.17632/xzr59ngmpz
title: Southern Ocean CO2 Machine Learning products (SOCOML)

description: We present a comprehensive, quality-controlled reconstruction of key carbonate system parameters in the Southern Ocean interior—including total alkalinity (TA), dissolved inorganic carbon (DIC), pH (total scale), nitrate (NO3), phosphate (PO4), silicate (SiO4), anthropogenic carbon (Cₐₙₜ), and aragonite saturation (Ωₐᵣ)—by leveraging machine learning techniques (ESPER_NN) and integrating all available Argo float profiles with ship-based survey data. The resulting datasets are gridded at 1°×1° horizontal resolution and 84 vertical pressure levels (0-5,600 dbar), and are provided as distinct climatological products: the Float Grid (using all Argo float profiles) and the All-Data Grid (integrating all available Argo and ship-based observations). The Float Grid is further separated into the Non-O₂-Float Grid (limited to Core Argo floats) and O₂-Float Grid (limited to oxygen-measured Biogeochemical Argo floats). Each gridded product is accompanied by uncertainty estimates. The climatological products covers nearly the whole Sothern Ocean based on direct measurements instead of applying interpolating mapping methods, thereby providing a more robust result. Model performance is assessed through cross-comparison of Argo and shipboard measurements.
DOI: 10.17632/xzr59ngmpz.2
title: Southern Ocean CO2 Machine Learning products (SOCOML)

description: We present a comprehensive, quality-controlled reconstruction of key carbonate system parameters in the Southern Ocean interior—including total alkalinity (TA), dissolved inorganic carbon (DIC), pH (total scale), nitrate (NO3), phosphate (PO4), silicate (SiO4), anthropogenic carbon (Cₐₙₜ), and aragonite saturation (Ωₐᵣ)—by leveraging machine learning techniques (ESPER_NN) and integrating all available Argo float profiles with ship-based survey data. The resulting datasets are gridded at 1°×1° horizontal resolution and 84 vertical pressure levels (0-5,600 dbar), and are provided as distinct climatological products: the Float Grid (using all Argo float profiles) and the All-Data Grid (integrating all available Argo and ship-based observations). The Float Grid is further separated into the Non-O₂-Float Grid (limited to Core Argo floats) and O₂-Float Grid (limited to oxygen-measured Biogeochemical Argo floats). Each gridded product is accompanied by uncertainty estimates. The climatological products covers nearly the whole Sothern Ocean based on direct measurements instead of applying interpolating mapping methods, thereby providing a more robust result. Model performance is assessed through cross-comparison of Argo and shipboard measurements.
DOI: 10.17632/53znhg8p9n
title: Dataset for Drone Problem Identification and Severity Estimation

description: This dataset contains a collection of drone flight log messages that was acquired from publicly accessible sources on Mendeley Data [1] and AirData [2]. This dataset consists of two subtasks: binary problem identification and multiclass problem severity classification. The former task used only the collection of log messages from Mendeley Data [1], and the later task used the merged collection of log messages from both sources. Each subtask has train and test split with 80:20 ratio generated with stratified sampling. This dataset covers a diverse drone models across various industrial sectors. Since the log messages are human-readable, this dataset can be used to develop NLP-based solutions to find problem-indicating log records and assist in forensic investigation.
DOI: 10.17632/53znhg8p9n.1
title: Dataset for Drone Problem Identification and Severity Estimation

description: This dataset contains a collection of drone flight log messages that was acquired from publicly accessible sources on Mendeley Data [1] and AirData [2]. This dataset consists of two subtasks: binary problem identification and multiclass problem severity classification. The former task used only the collection of log messages from Mendeley Data [1], and the later task used the merged collection of log messages from both sources. Each subtask has train and test split with 80:20 ratio generated with stratified sampling. This dataset covers a diverse drone models across various industrial sectors. Since the log messages are human-readable, this dataset can be used to develop NLP-based solutions to find problem-indicating log records and assist in forensic investigation.
DOI: 10.13140/rg.2.2.16754.77766
title: PolyhedraFiles
DOI: 10.17632/j45g5fywsz
title: effects of grazing and salinization on soil properties and plant community traits

description: effects of grazing and salinization on soil properties and plant community traits
DOI: 10.17632/j45g5fywsz.1
title: effects of grazing and salinization on soil properties and plant community traits

description: effects of grazing and salinization on soil properties and plant community traits
DOI: 10.17632/rdfc9hb88h
title: Development of a Mucosal Immune-Enhancing Oral Vaccine Against Porcine Epidemic Diarrhea Virus Using Lactobacillus paracasei

description: We attempted to enhance the specific immune ability of the mucosa, Lactobacillus paracasei served as the host strain to express the fusion of the protective antigen S1 of PEDV, the M cell-targeting peptide Co1, the dendritic cell-targeting peptides (6aa), and the mucosal immune adjuvant LTB, thereby obtaining a candidate strain pPG-Co1-6aa-S1-LTB/27-2. Pregnant mice that received oral immunization with recombinant microorganisms demonstrated a notable increase in serum IgG antibodies that are specific to anti-PEDV, in addition to intestinal mucus and fecal SIgA antibodies, both of which exhibited in vitro neutralizing activity. Additionally, pregnant mice had considerably higher serum levels of IFN-γ, IL-2, IL-4, and IL-10. Notably, the level of anti-PEDV specific SIgA antibodies of the newborn mice delivered by the pregnant mice was also significantly elevated. The aforementioned findings show that the recombinant bacteria pPG-Co1-6aa-S1-LTB/27-2 can produce maternal antibodies and strongly stimulate humoral, cellular, and mucosal immune responses in pregnant mice.
Figure 1. Illustrative diagram showing the creation of recombinant plasmids.
Figure 2. Immunization protocol and sampling schedule.
Figure 3. Identification and protein expression analysis of recombinant L.paracasei 27-2. A. PCR identification of recombinant plasmids. M: Trans 2k plus DNA marker. B. Western blot analysis was used to confirm the fusion protein's expression. M: Pre-stained protein marker. C. Analysis of binding activity of recombinant lactobacillus expressing LTB protein.
Figure 4. Proteins from different species were presented on the surface of Lactobacillus paracasei.
Figure 5. Biological characterization analysis. A. Growth curve determination. B. The protein stability of the recombinant strains was assessed through Western blot analysis.
Figure 6. Anti-PEDV-specific IgG antibody levels in the serum, anti-PEDV-specific SIgA antibody levels in the intestinal mucus and fecal are listed in A, B, and C, respectively.
Figure 7. Measurement of neutralizing activity in intestinal serum IgG and mucus SIgA antibody levels in vaccinated pregnant mice.
Figure 8. Measure the blood cytokine levels in pregnant mice that have received recombinant strains and PBS vaccinations. The mean ± SEM of three separate experiments is used to illustrate the results.
Figure 9. Quantities of anti-PEDV specific SIgA antibodies in the intestinal mucus of neonatal mice.
DOI: 10.17632/rdfc9hb88h.5
title: Development of a Mucosal Immune-Enhancing Oral Vaccine Against Porcine Epidemic Diarrhea Virus Using Lactobacillus paracasei

description: We attempted to enhance the specific immune ability of the mucosa, Lactobacillus paracasei served as the host strain to express the fusion of the protective antigen S1 of PEDV, the M cell-targeting peptide Co1, the dendritic cell-targeting peptides (6aa), and the mucosal immune adjuvant LTB, thereby obtaining a candidate strain pPG-Co1-6aa-S1-LTB/27-2. Pregnant mice that received oral immunization with recombinant microorganisms demonstrated a notable increase in serum IgG antibodies that are specific to anti-PEDV, in addition to intestinal mucus and fecal SIgA antibodies, both of which exhibited in vitro neutralizing activity. Additionally, pregnant mice had considerably higher serum levels of IFN-γ, IL-2, IL-4, and IL-10. Notably, the level of anti-PEDV specific SIgA antibodies of the newborn mice delivered by the pregnant mice was also significantly elevated. The aforementioned findings show that the recombinant bacteria pPG-Co1-6aa-S1-LTB/27-2 can produce maternal antibodies and strongly stimulate humoral, cellular, and mucosal immune responses in pregnant mice.
Figure 1. Illustrative diagram showing the creation of recombinant plasmids.
Figure 2. Immunization protocol and sampling schedule.
Figure 3. Identification and protein expression analysis of recombinant L.paracasei 27-2. A. PCR identification of recombinant plasmids. M: Trans 2k plus DNA marker. B. Western blot analysis was used to confirm the fusion protein's expression. M: Pre-stained protein marker. C. Analysis of binding activity of recombinant lactobacillus expressing LTB protein.
Figure 4. Proteins from different species were presented on the surface of Lactobacillus paracasei.
Figure 5. Biological characterization analysis. A. Growth curve determination. B. The protein stability of the recombinant strains was assessed through Western blot analysis.
Figure 6. Anti-PEDV-specific IgG antibody levels in the serum, anti-PEDV-specific SIgA antibody levels in the intestinal mucus and fecal are listed in A, B, and C, respectively.
Figure 7. Measurement of neutralizing activity in intestinal serum IgG and mucus SIgA antibody levels in vaccinated pregnant mice.
Figure 8. Measure the blood cytokine levels in pregnant mice that have received recombinant strains and PBS vaccinations. The mean ± SEM of three separate experiments is used to illustrate the results.
Figure 9. Quantities of anti-PEDV specific SIgA antibodies in the intestinal mucus of neonatal mice.
DOI: 10.17632/6crzxmh4kn
title: Dataset to “novel_circ_002651 regulates the immune defense of eastern honeybee larvae against fungal invasion through sponging miR-6001-y”

description: This study aims to characterize the regulatory functions of a previously identified circRNA (novel_circ_002651, ac2651) and its key target miRNA (ace-miR-6001-y), in eastern honeybee worker larvae respondi ng to infection by Ascosphaera apis:
Figure 1. (A) Regulatory network between ac2651 and target miRNAs. (B) Agarose gel electrophoresis for the amplified product from ac2651. (C) Peak diagram of Sanger sequencing of the amplified fragment from ac2651, the black arrow indicates the back-splicing site. (D) Agarose gel electrophoresis for the amplified product from ace-miR-6001-y. (E) peak diagram of Sanger sequencing of the amplified fragment from ace-miR-6001-y. (F, G) Relative expression levels of ac2651 and ace-miR-6001-y in the guts of 4-, 5-, and 6-day-old larvae inoculated with A. apis. 
Figure 2. (A) Loop graph of GO terms annotated by target mRNAs. (B) Loop graph of KEGG pathways annotated by target mRNAs. (C) Regulatory network between ace-miR-6001-y and immune pathway-related target DEmRNAs.
Figure 3. (A) Relative expression level of ac2651 following feeding specific siRNA. (B) Relative expression level of 3 immune genes in the larval guts after silencing ac2651. (C) Relative expression level of 3 genes relative to fungal proliferation after silencing ac2651. (D) Larval survival rate following silencing ac2651. (E) Larval chalkbrood incidence following silencing ac2651.
Figure 4. (A, F) Relative expression level of ace-miR-6001-y in the larval guts after feeding mimic and inhibitor. (B, G) Relative expression levels of 3 host immune genes following ace-miR-6001-y overexpression and knockdown. (C, H) Relative expression levels of 3 genes relevant to fungal proliferation following ace-miR-6001-y overexpression and knockdown. (D, I) Host survival rate following overexpression and knockdown of ace-miR-6001-y. (E, J) Host chalkbrood incidence following ace-miR-6001-y overexpression and knockdown.
Figure 5. (A, F) agarose gel electrophoresis for PCR amplification products. (B, G) Sanger sequencing result of the target fragment. (C, D) peak diagrams of Sanger sequencing of recombinant plasmids pmirGLO-ac2651-miR-6001-wt and pmirGLO-ac2651-miR-6001-mut. (E) Verification of binding relationship between ac2651 and ace-miR-6001-y. (H, I) peak diagrams of Sanger sequencing of recombinant plasmids pmirGLO-miR-6001-14-3-3ζ-wt and pmirGLO-miR-6001-14-3-3ζ-mut. (J) Verification of binding relationship between ace-miR-6001-y and Ac14-3-3ζ. 
Figure 6. (A, B) Relative expression levels of ace-miR-6001-y and Ac14-3-3ζ after silencing ac2651. (C) Relative expression level of Ac14-3-3ζ following ace-miR-6001-y knockdown. (D) Relative expression level of Ac14-3-3ζ after simultaneously silencing ac2651 interference and knocking down ace-miR-6001-y.
Figure 7. (A) Relative expression level of 3 immune genes in the larval guts. (B) Host survival rate. (C) Relative expression levels of 3 genes related to fungal proliferation. (D) Host chalkbrood incidence.
DOI: 10.15468/dl.g684vr
title: Occurrence Download

description: A dataset containing 5617 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence)",
 "Geometry POLYGON((81.64269 -60.79916,195.49156 -60.79916,195.49156 14.16812,81.64269 14.16812,81.64269 -60.79916))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Natator depressus"
 ]
}

 The dataset includes 5617 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002921-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/6crzxmh4kn.2
title: Dataset to “novel_circ_002651 regulates the immune defense of eastern honeybee larvae against fungal invasion through sponging miR-6001-y”

description: This study aims to characterize the regulatory functions of a previously identified circRNA (novel_circ_002651, ac2651) and its key target miRNA (ace-miR-6001-y), in eastern honeybee worker larvae respondi ng to infection by Ascosphaera apis:
Figure 1. (A) Regulatory network between ac2651 and target miRNAs. (B) Agarose gel electrophoresis for the amplified product from ac2651. (C) Peak diagram of Sanger sequencing of the amplified fragment from ac2651, the black arrow indicates the back-splicing site. (D) Agarose gel electrophoresis for the amplified product from ace-miR-6001-y. (E) peak diagram of Sanger sequencing of the amplified fragment from ace-miR-6001-y. (F, G) Relative expression levels of ac2651 and ace-miR-6001-y in the guts of 4-, 5-, and 6-day-old larvae inoculated with A. apis. 
Figure 2. (A) Loop graph of GO terms annotated by target mRNAs. (B) Loop graph of KEGG pathways annotated by target mRNAs. (C) Regulatory network between ace-miR-6001-y and immune pathway-related target DEmRNAs.
Figure 3. (A) Relative expression level of ac2651 following feeding specific siRNA. (B) Relative expression level of 3 immune genes in the larval guts after silencing ac2651. (C) Relative expression level of 3 genes relative to fungal proliferation after silencing ac2651. (D) Larval survival rate following silencing ac2651. (E) Larval chalkbrood incidence following silencing ac2651.
Figure 4. (A, F) Relative expression level of ace-miR-6001-y in the larval guts after feeding mimic and inhibitor. (B, G) Relative expression levels of 3 host immune genes following ace-miR-6001-y overexpression and knockdown. (C, H) Relative expression levels of 3 genes relevant to fungal proliferation following ace-miR-6001-y overexpression and knockdown. (D, I) Host survival rate following overexpression and knockdown of ace-miR-6001-y. (E, J) Host chalkbrood incidence following ace-miR-6001-y overexpression and knockdown.
Figure 5. (A, F) agarose gel electrophoresis for PCR amplification products. (B, G) Sanger sequencing result of the target fragment. (C, D) peak diagrams of Sanger sequencing of recombinant plasmids pmirGLO-ac2651-miR-6001-wt and pmirGLO-ac2651-miR-6001-mut. (E) Verification of binding relationship between ac2651 and ace-miR-6001-y. (H, I) peak diagrams of Sanger sequencing of recombinant plasmids pmirGLO-miR-6001-14-3-3ζ-wt and pmirGLO-miR-6001-14-3-3ζ-mut. (J) Verification of binding relationship between ace-miR-6001-y and Ac14-3-3ζ. 
Figure 6. (A, B) Relative expression levels of ace-miR-6001-y and Ac14-3-3ζ after silencing ac2651. (C) Relative expression level of Ac14-3-3ζ following ace-miR-6001-y knockdown. (D) Relative expression level of Ac14-3-3ζ after simultaneously silencing ac2651 interference and knocking down ace-miR-6001-y.
Figure 7. (A) Relative expression level of 3 immune genes in the larval guts. (B) Host survival rate. (C) Relative expression levels of 3 genes related to fungal proliferation. (D) Host chalkbrood incidence.
DOI: 10.17632/ntc3xd4hk5
title: Haifa microplastics community gardens data

description: Raw data used to create tables and graphs for publication about the distribution of microplastics found in community gardens throughout the city of Haifa. Includes raw .CSVs and .xlsx used in analysis.
DOI: 10.17632/ntc3xd4hk5.1
title: Haifa microplastics community gardens data

description: Raw data used to create tables and graphs for publication about the distribution of microplastics found in community gardens throughout the city of Haifa. Includes raw .CSVs and .xlsx used in analysis.
DOI: 10.17632/vmhdthtzxg
title: Kilic & Tuzel - Investing in Misallocation (Final)

description: This folder contains the replication code for the model estimation and empirical analysis, along with the pseudo-data used in the empirical analysis for “Investing in Misallocation” by Kilic and Tuzel.
DOI: 10.5281/zenodo.16912444
title: DrugReflector model checkpoints

description: DrugReflector is an ensemble of three multi-layer perceptron classifiers trained on Connectivity Map transcriptional signatures to predict compound classes from transcriptional signatures. The training set was partitioned into three non-overlapping splits, and each model was trained on two of the three splits using individual perturbation signatures as inputs (without replicate averaging).

This DOI contains the resulting three torch model checkpoints, one for each split-trained model.
DOI: 10.5281/zenodo.17437512
title: DrugReflector model checkpoints

description: DrugReflector is an ensemble of three multi-layer perceptron classifiers trained on Connectivity Map transcriptional signatures to predict compound classes from transcriptional signatures. The training set was partitioned into three non-overlapping splits, and each model was trained on two of the three splits using individual perturbation signatures as inputs (without replicate averaging).

This DOI contains the resulting three torch model checkpoints, one for each split-trained model.
DOI: 10.17632/vmhdthtzxg.1
title: Kilic & Tuzel - Investing in Misallocation (Final)

description: This folder contains the replication code for the model estimation and empirical analysis, along with the pseudo-data used in the empirical analysis for “Investing in Misallocation” by Kilic and Tuzel.
DOI: 10.17632/n2pnkd74df
title: Mitochondrial Metabolic Reprogramming along with NRF2/KEAP1-mediated Antioxidant Mechanisms Drive Temozolomide Resistance in Glioblastoma Multiforme

description: The repository contains three main files: (1) a .zip folder with the raw chromatograms from the experiments (blank samples, qualitative control, and samples); (2) the retention index file for matabolite annotation (Alkanes-Retention-index.txt); and (3) an Excel file reporting the extracted intensities, quant mass, spectral similarities, putative annotations, metabolite spectra, and all statistical outputs (PCA, OPLS-DA, t-Test, Volcano Plot data, enrichment analysis etc.).
DOI: 10.17632/n2pnkd74df.2
title: Mitochondrial Metabolic Reprogramming along with NRF2/KEAP1-mediated Antioxidant Mechanisms Drive Temozolomide Resistance in Glioblastoma Multiforme

description: The repository contains three main files: (1) a .zip folder with the raw chromatograms from the experiments (blank samples, qualitative control, and samples); (2) the retention index file for matabolite annotation (Alkanes-Retention-index.txt); and (3) an Excel file reporting the extracted intensities, quant mass, spectral similarities, putative annotations, metabolite spectra, and all statistical outputs (PCA, OPLS-DA, t-Test, Volcano Plot data, enrichment analysis etc.).
DOI: 10.17632/fk5s8bt7s7
title: Dataset for snake predation analyses

description: Dataset for snake predation analyses on cavity-nesting birds using artificial nest boxes
DOI: 10.17632/fk5s8bt7s7.1
title: Dataset for snake predation analyses

description: Dataset for snake predation analyses on cavity-nesting birds using artificial nest boxes
DOI: 10.5281/zenodo.17456301
title: Simulation and Design Files for "Rational Design of DNA Nanocarriers through Sequence and Length Control"

description: This dataset contains the coarse-grained simulation and design files supporting the study “Rational Design of DNA Nanocarriers through Sequence and Length Control.” The archive includes oxDNA configuration, topology, and parameter files (.conf, .top, .par) used for the simulations of nanocarriers with varying linker sequences and lengths, as well as cadnano design files for the initial DNA constructs.

These data allow reproduction and extension of the molecular dynamics simulations and structural analyses reported in the article. All files are organized by linker type (A–T, C–G, mixed) and length.

Software required: oxDNA (https://dna.physics.ox.ac.uk) and cadnano (https://cadnano.org).
DOI: 10.5281/zenodo.17456302
title: Simulation and Design Files for "Rational Design of DNA Nanocarriers through Sequence and Length Control"

description: This dataset contains the coarse-grained simulation and design files supporting the study “Rational Design of DNA Nanocarriers through Sequence and Length Control.” The archive includes oxDNA configuration, topology, and parameter files (.conf, .top, .par) used for the simulations of nanocarriers with varying linker sequences and lengths, as well as cadnano design files for the initial DNA constructs.

These data allow reproduction and extension of the molecular dynamics simulations and structural analyses reported in the article. All files are organized by linker type (A–T, C–G, mixed) and length.

Software required: oxDNA (https://dna.physics.ox.ac.uk) and cadnano (https://cadnano.org).