cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10798966
title: LRO Craters (COCO)

description: This remarkable dataset of lunar images captured by the LRO Camera has been meticulously labeled in COCO format for object detection tasks in computer vision. The COCO annotation format provides a standardized way of describing objects in the images, including their locations and class labels, enabling machine learning algorithms to learn to recognize and detect objects in the images more accurately.


This dataset captures a wide variety of lunar features, including craters, mountains, and other geological formations, all labeled with precise and consistent COCO annotation. The dataset's comprehensive coverage of craters and other geological features on the Moon provides a treasure trove of data and insights into the evolution of our closest celestial neighbor.


The COCO annotation format is particularly well-suited for handling complex scenes with multiple objects, occlusions, and overlapping objects. With the precise labeling of objects provided by COCO annotation, this dataset enables researchers and scientists to train machine learning algorithms to automatically detect and analyze these features in large datasets.


In conclusion, this valuable dataset of lunar images labeled in COCO annotation format provides a powerful tool for research and discovery in the field of planetary science. With its comprehensive coverage and precise labeling of lunar features, it offers a wealth of data and insights into the evolution of the Moon's landscape, facilitating research and understanding of this enigmatic celestial body.
DOI: 10.5281/zenodo.10799005
title: LRO Craters (COCO)

description: This remarkable dataset of lunar images captured by the LRO Camera has been meticulously labeled in COCO format for object detection tasks in computer vision. The COCO annotation format provides a standardized way of describing objects in the images, including their locations and class labels, enabling machine learning algorithms to learn to recognize and detect objects in the images more accurately.


This dataset captures a wide variety of lunar features, including craters, mountains, and other geological formations, all labeled with precise and consistent COCO annotation. The dataset's comprehensive coverage of craters and other geological features on the Moon provides a treasure trove of data and insights into the evolution of our closest celestial neighbor.


The COCO annotation format is particularly well-suited for handling complex scenes with multiple objects, occlusions, and overlapping objects. With the precise labeling of objects provided by COCO annotation, this dataset enables researchers and scientists to train machine learning algorithms to automatically detect and analyze these features in large datasets.


In conclusion, this valuable dataset of lunar images labeled in COCO annotation format provides a powerful tool for research and discovery in the field of planetary science. With its comprehensive coverage and precise labeling of lunar features, it offers a wealth of data and insights into the evolution of the Moon's landscape, facilitating research and understanding of this enigmatic celestial body.
DOI: 10.5281/zenodo.10807399
title: LRO Craters (COCO)

description: This remarkable dataset of lunar images captured by the LRO Camera has been meticulously labeled in COCO format for object detection tasks in computer vision. The COCO annotation format provides a standardized way of describing objects in the images, including their locations and class labels, enabling machine learning algorithms to learn to recognize and detect objects in the images more accurately.


This dataset captures a wide variety of lunar features, including craters, mountains, and other geological formations, all labeled with precise and consistent COCO annotation. The dataset's comprehensive coverage of craters and other geological features on the Moon provides a treasure trove of data and insights into the evolution of our closest celestial neighbor.


The COCO annotation format is particularly well-suited for handling complex scenes with multiple objects, occlusions, and overlapping objects. With the precise labeling of objects provided by COCO annotation, this dataset enables researchers and scientists to train machine learning algorithms to automatically detect and analyze these features in large datasets.


In conclusion, this valuable dataset of lunar images labeled in COCO annotation format provides a powerful tool for research and discovery in the field of planetary science. With its comprehensive coverage and precise labeling of lunar features, it offers a wealth of data and insights into the evolution of the Moon's landscape, facilitating research and understanding of this enigmatic celestial body.
DOI: 10.5281/zenodo.7774054
title: LRO Craters (COCO)

description: This remarkable dataset of lunar images captured by the LRO Camera has been meticulously labeled in COCO format for object detection tasks in computer vision. The COCO annotation format provides a standardized way of describing objects in the images, including their locations and class labels, enabling machine learning algorithms to learn to recognize and detect objects in the images more accurately.


This dataset captures a wide variety of lunar features, including craters, mountains, and other geological formations, all labeled with precise and consistent COCO annotation. The dataset's comprehensive coverage of craters and other geological features on the Moon provides a treasure trove of data and insights into the evolution of our closest celestial neighbor.


The COCO annotation format is particularly well-suited for handling complex scenes with multiple objects, occlusions, and overlapping objects. With the precise labeling of objects provided by COCO annotation, this dataset enables researchers and scientists to train machine learning algorithms to automatically detect and analyze these features in large datasets.


In conclusion, this valuable dataset of lunar images labeled in COCO annotation format provides a powerful tool for research and discovery in the field of planetary science. With its comprehensive coverage and precise labeling of lunar features, it offers a wealth of data and insights into the evolution of the Moon's landscape, facilitating research and understanding of this enigmatic celestial body.
DOI: 10.5281/zenodo.7774055
title: LRO Craters (COCO)

description: This remarkable dataset of lunar images captured by the LRO Camera has been meticulously labeled in COCO format for object detection tasks in computer vision. The COCO annotation format provides a standardized way of describing objects in the images, including their locations and class labels, enabling machine learning algorithms to learn to recognize and detect objects in the images more accurately. This dataset captures a wide variety of lunar features, including craters, mountains, and other geological formations, all labeled with precise and consistent COCO annotation. The dataset's comprehensive coverage of craters and other geological features on the Moon provides a treasure trove of data and insights into the evolution of our closest celestial neighbor. The COCO annotation format is particularly well-suited for handling complex scenes with multiple objects, occlusions, and overlapping objects. With the precise labeling of objects provided by COCO annotation, this dataset enables researchers and scientists to train machine learning algorithms to automatically detect and analyze these features in large datasets. In conclusion, this valuable dataset of lunar images labeled in COCO annotation format provides a powerful tool for research and discovery in the field of planetary science. With its comprehensive coverage and precise labeling of lunar features, it offers a wealth of data and insights into the evolution of the Moon's landscape, facilitating research and understanding of this enigmatic celestial body.
DOI: 10.6084/m9.figshare.22976144.v1
title: Molecular Near-Infrared Triplet-Triplet Annihilation Upconversion with Eigen Oxygen Immunity

description: The data include relevant photophysical tests and kinetic models, as well as relevant particle size characterization of nanomaterials
DOI: 10.6084/m9.figshare.22976144
title: Molecular Near-Infrared Triplet-Triplet Annihilation Upconversion with Eigen Oxygen Immunity

description: The data include relevant photophysical tests and kinetic models, as well as relevant particle size characterization of nanomaterials
DOI: 10.6084/m9.figshare.24681372
title: A Ce-CuZn catalyst with abundant Cu/Zn-OV-Ce active sites for CO2 hydrogenation to methanol

description: Source Data-20240219; Figshare DOI: https://doi.org/10.6084/m9.figshare.25129247
DOI: 10.6084/m9.figshare.24681372.v1
title: A Ce-CuZn catalyst with abundant Cu/Zn-OV-Ce active sites for CO2 hydrogenation to methanol

description: Source Data-20240219; Figshare DOI: https://doi.org/10.6084/m9.figshare.25129247
DOI: 10.6084/m9.figshare.22723868.v1
title: Simultaneous proteome localization and turnover analysis reveals spatiotemporal features of protein homeostasis disruptions

description: Supplementary Data 1 – 10 for Currie et al.
DOI: 10.6084/m9.figshare.22723868
title: Simultaneous proteome localization and turnover analysis reveals spatiotemporal features of protein homeostasis disruptions

description: Supplementary Data 1 – 10 for Currie et al.
DOI: 10.6084/m9.figshare.24813915
title: Identification of gene regulatory networks affected across drug-resistant epilepsies

description: Supplementary Table 1: Gene module summary. Supplementary Table 2: Genes and modules. Supplementary Table 3: Differential coexpression. Supplementary Table 4: Functional annotation . Supplementary Table 5: Summary cohort comparison. Supplementary Table 6: Sample metadata information. Supplementary Table 7: Full list of genes included in the target gene panel. Supplementary Table 8: Differential expression results for KCC2 and NKCC1 across the different cohort. Supplementary Table 9: Differential expression results on genes belonging to “GABA signalling pathway” (GO:0007214) across the different comparison (mTLE, FCD2b, TSC, and MTOR). Supplementary Table 10: Differential expression results on genes belonging to “glutamate receptor signalling pathway” (GO:0007215) across the different comparison (mTLE, FCD2b, TSC, and MTOR). Supplementary Table 11: Primers and sequence used for RT-PCR.
DOI: 10.6084/m9.figshare.24813915.v1
title: Identification of gene regulatory networks affected across drug-resistant epilepsies

description: Supplementary Table 1: Gene module summary. Supplementary Table 2: Genes and modules. Supplementary Table 3: Differential coexpression. Supplementary Table 4: Functional annotation . Supplementary Table 5: Summary cohort comparison. Supplementary Table 6: Sample metadata information. Supplementary Table 7: Full list of genes included in the target gene panel. Supplementary Table 8: Differential expression results for KCC2 and NKCC1 across the different cohort. Supplementary Table 9: Differential expression results on genes belonging to “GABA signalling pathway” (GO:0007214) across the different comparison (mTLE, FCD2b, TSC, and MTOR). Supplementary Table 10: Differential expression results on genes belonging to “glutamate receptor signalling pathway” (GO:0007215) across the different comparison (mTLE, FCD2b, TSC, and MTOR). Supplementary Table 11: Primers and sequence used for RT-PCR.
DOI: 10.6084/m9.figshare.25390729
title: IBD gut microbiome data: Culturomics,16S rRNA metagenomics, and reproducible R code

description: Culturomics data from inflammatory bowel disease patients, 16S rRNA amplicon sequencing data, and reproducible R code are included. These data relate to the findings of a manuscript titled 'A combined culturomics and metagenomics perspective on gut microbiota in inflammatory bowel disease'. (unpublished, March 2024)
DOI: 10.6084/m9.figshare.24654966
title: <b>Global contribution of invertebrates to forest litter decomposition</b>

description: Forest litter decomposition is an essential component of global carbon and nutrient turnover. Invertebrates play important roles in litter decomposition, but the regional pattern of their effects is poorly understood. We examined 476 case studies across 93 sites and performed a meta-analysis to estimate regional effects of invertebrates on forest litter decomposition. We then assessed how invertebrate diversity, climate and soil pH drive regional variations in invertebrate-mediated decomposition. We found that (1) invertebrate contributions to litter decomposition are 1.4 times higher in tropical and subtropical forests than forests elsewhere, with an overall contribution of 31% to global forest litter decomposition; and (2) termite diversity, together with warm, humid and acidic environments in the tropics and subtropics are positively associated with forest litter decomposition by invertebrates. Our results demonstrate the significant difference in invertebrate effects on mediating forest litter decomposition among regions. We demonstrate, also, the significance of termites in driving litter mass loss in the tropics and subtropics. These results are particularly pertinent in the tropics and subtropics where climate change and human disturbance threaten invertebrate biodiversity and the ecosystem services it provides.
DOI: 10.25345/c5p84467q
title: MassIVE MSV000094292 - synthesized of 1H,1Cl-PFOA from 1H,1H-PFOA or from 6:2 FTOH.
title: synthesized of 1H,1Cl-PFOA from 1H,1H-PFOA or from 6:2 FTOH.
DOI: 10.4225/06/4ed6b979ebge6
title: Input and selected output files for simulations of sunset yellow dimers
DOI: 10.4225/06/4ed6b979ebhe7
title: Input and selected output files for simulations of benzene adsorbed to the Cu (111) surface
DOI: 10.4225/06/4ed6b979ebfd5
title: Calculated structures and energies of molecular crystals using dispersion corrected density functionals
DOI: 10.6084/m9.figshare.25376317
title: FIGURE

description: video for TX
DOI: 10.6084/m9.figshare.25376317.v2
title: Source data —— Redox-neutral electrochemical decontamination of hypersaline wastewater with high technology readiness level.

description: Source data-Redox-neutral electrochemical decontamination of hypersaline wastewater with high technology readiness level.
DOI: 10.6084/m9.figshare.25376317.v3
title: FIGURE

description: video for TX
DOI: 10.21227/pp31-x251
title: MNET2024

description: Based on the research requirements, we have created the MNET2024 (Malicious and Encrypted Traffic 2024) dataset, which satisfies the conditions of encrypted benign data and encrypted malicious data. The dataset includes 10 types of benign encrypted data, such as P2P, web browsing, and email, which are collected from real traffic sources. It also includes ten types of malicious encrypted traffic sourced from the Stratosphere Lab’s [14] open-source malicious traffic dataset, such as Dridex and Emotet. For application types with a limited number of samples, corresponding malware is executed in a relatively secure sandbox environment to supplement the dataset.
DOI: 10.5281/zenodo.10798944
title: ESAT-6 undergoes self-association at phagosomal pH and an ESAT-6 specific nanobody restricts M. tuberculosis growth in macrophages

description: Mycobacterium tuberculosis (Mtb) is known to survive within macrophages by compromising the integrity of the phagosomal compartment in which it resides. This activity primarily relies on the ESX-1 secretion system, predominantly involving the protein duo ESAT-6 and CFP-10. CFP-10 likely acts as a chaperone, while ESAT-6 likely disrupts phagosomal membrane stability via a largely unknown mechanism. we employ a series of biochemical analyses, protein modeling techniques, and a novel ESAT-6-specific nanobody to gain insight into the ESAT-6’s mode of action. First, we measure the binding kinetics of the tight 1:1 complex formed by ESAT-6 and CFP-10 at neutral pH. Subsequently, we demonstrate a rapid self-association of ESAT-6 into large complexes under acidic conditions, leading to the identification of a stable tetrameric ESAT-6 species. Using molecular dynamics simulations, we pinpoint the most probable interaction interface. Furthermore, we show that cytoplasmic expression of an anti-ESAT-6 nanobody blocks Mtb replication, thereby underlining the pivotal role of ESAT-6 in intracellular survival. Together, these data suggest that ESAT-6 acts by a pH dependent mechanism to establish two-way communication between the cytoplasm and the Mtb-containing phagosome.
DOI: 10.5281/zenodo.10798945
title: ESAT-6 undergoes self-association at phagosomal pH and an ESAT-6 specific nanobody restricts M. tuberculosis growth in macrophages

description: Mycobacterium tuberculosis (Mtb) is known to survive within macrophages by compromising the integrity of the phagosomal compartment in which it resides. This activity primarily relies on the ESX-1 secretion system, predominantly involving the protein duo ESAT-6 and CFP-10. CFP-10 likely acts as a chaperone, while ESAT-6 likely disrupts phagosomal membrane stability via a largely unknown mechanism. we employ a series of biochemical analyses, protein modeling techniques, and a novel ESAT-6-specific nanobody to gain insight into the ESAT-6’s mode of action. First, we measure the binding kinetics of the tight 1:1 complex formed by ESAT-6 and CFP-10 at neutral pH. Subsequently, we demonstrate a rapid self-association of ESAT-6 into large complexes under acidic conditions, leading to the identification of a stable tetrameric ESAT-6 species. Using molecular dynamics simulations, we pinpoint the most probable interaction interface. Furthermore, we show that cytoplasmic expression of an anti-ESAT-6 nanobody blocks Mtb replication, thereby underlining the pivotal role of ESAT-6 in intracellular survival. Together, these data suggest that ESAT-6 acts by a pH dependent mechanism to establish two-way communication between the cytoplasm and the Mtb-containing phagosome.
DOI: 10.5281/zenodo.10807439
title: Data of 'Enhancement of Magnonic Frequency Combs by Exceptional Points'
DOI: 10.5281/zenodo.10807440
title: Data of 'Enhancement of Magnonic Frequency Combs by Exceptional Points'
DOI: 10.5281/zenodo.10807407
title: Topics in the Romanian proustian novel 1925-1935

description: This dataset gathers information regarding the textual neighbours of the idea of home in the novels of Romanian authors Hortensia Papadat-Bengescu, Camil Petrescu, and Anton Holban (nouns, verbs, sentimental markers, other stats). The data is in the original language (Romanian) and it was extracted from the first editions of the novels (published between 1925 and 1934) with the aid of the TXM platform. 
description: This work was supported by Babeș-Bolyai University, grant number SRG-UBB no. 32887/21.06.2023, "Close Reading Modernism with Computers. Mining Romanian Canonical Novels with Digital Tools"
DOI: 10.5281/zenodo.10807408
title: Topics in the Romanian proustian novel 1925-1935

description: This dataset gathers information regarding the textual neighbours of the idea of home in the novels of Romanian authors Hortensia Papadat-Bengescu, Camil Petrescu, and Anton Holban (nouns, verbs, sentimental markers, other stats). The data is in the original language (Romanian) and it was extracted from the first editions of the novels (published between 1925 and 1934) with the aid of the TXM platform. 
description: This work was supported by Babeș-Bolyai University, grant number SRG-UBB no. 32887/21.06.2023, "Close Reading Modernism with Computers. Mining Romanian Canonical Novels with Digital Tools"
DOI: 10.6084/m9.figshare.25296202
title: Data and code from: Fire facilitates ground layer plant diversity in a Miombo ecosystem

description: Data and code used in Wieczorkowski, J.D., Lehmann, C.E.R., Archibald, S., Banda, S., Goyder, D.J., Kaluwe, M., Kapinga, K., Larridon, I., Mashau, A.C., Phiri, E., Syampungani, S. (2024) Fire facilitates ground layer plant diversity in a Miombo ecosystem. Annals of Botany. doi.org/10.1093/aob/mcae035
DOI: 10.34740/kaggle/dsv/7822079
title: Egypt Gold Prices | Daily Updated
DOI: 10.34808/svhv-wj63
title: Sigma profiles of DES components

description: The Sigma profiles for DES components created by the COSMO-RS. 
- TBACl                                      - ChCl                                 - TEACl                                - PG                                     - EG                               - EGDMA                                - Methanethiol                       - Etanotiol                                - 1,6-Hexanediol
DOI: 10.4225/75/56c66d087a3c3
title: Variability in the carbon storage of seagrass habitats and its implications for global estimates of Blue Carbon ecosystem service [dataset]

description: The database compiles published data (in Lavery et al. 2013, PLoS ONE 8(9): e73748. doi:10.1371/journal.pone.0073748) on biogeochemical variables (organic matter, organic carbon and CO3 contents, and stable carbon isotope signatures of the organic carbon) in sediment core from seagrass meadows in Australia. The cores studied were up to 29 cm long, and ecompass tropical, subtropical and temperate seagrass meadows in intertidal and subtidal habitats. Enquiries about the dataset may be sent to Paul Lavery p.lavery@ecu.edu.au.
DOI: 10.5517/ccdc.csd.cc24rk1j
title: CCDC 1988837: Experimental Crystal Structure Determination

description: Related Article: Xiaoshu Qu, Zeyu Wang, Xiaoyu Weng, Jiaqi Geng, Yanyan Yang, Xuemei Li, Hua Jin, Shuping Liu, Qiang Zhang, Xiao-Yang Yu|2024|Inorg.Chim.Acta|566|122004|doi:10.1016/j.ica.2024.122004
description: Related Article: Xiao-Yang Yu, Sheng-Ling Li, Rui Zhang, Lu Gao, Tong Lu, Xue-Ling Cao, Hao Cui, Zhenyu Shi, Yuguo Zheng, Ying Yang|2020|Inorg.Chim.Acta|510|119717|doi:10.1016/j.ica.2020.119717
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: 10.4225/75/56c566831d41a
title: Seagrass Sediments Reveal The Long-term Deterioration Of An Estuarine Ecosystem [dataset]

description: The database compiles published data (in Serrano et al. 2016, Global Change Biology, doi:10.1111/gcb.13195) on temporal trends in biogeochemical variables in the Posidonia australis sediment core from Oyster Harbour, Western Australia. The core studied encompasses the last 500 years of history. Data on dry bulk density, carbonate content, sedimentso.serranogras@ecu.edu.au.
DOI: 10.4225/75/56c561fb1d419
title: Impact Of Mooring Activities On Carbon Stocks In Seagrass Meadows [dataset]

description: The database compiles published data (in Serrano et al. 2016, Scientific Reports, in press) on biogeochemical characteristics (density, organic carbon, calcium carbonate, stable carbon isotopes and sediment grain size) of sediments underneath seagrass meadows and adjacent un-vegetated patches after mooring disturbances in Rottnest Island (Perth, Western Australia). The dataset compiles data on biogeochemical sediment characteristics for a total of 16 cores, 50 cm-long (4 cores from seagrass meadows and 4 cores from adjacent bare sediments at Thompson Bay, and 4 cores from seagrass meadows and 4 cores from adjacent bare sediments at Stark Bay). Enquiries about the dataset may be sent to Oscar Serrano o.serranogras@ecu.edu.au.