cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.rrxnap
title: Occurrence Download

description: A dataset containing 19155 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (South Africa, Lesotho, Eswatini)",
 "TaxonKey is one of (Cyanomitra veroxii (A.Smith, 1831))",
 "BasisOfRecord is one of (Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1950",
 "OccurrenceStatus is Present",
 "DistanceFromCentroidInMeters is greater than or equal to 2000"
 ]
}

 The dataset includes 19155 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004370-250117142028555/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/3zv8mft5cn.1
title: LDHU3_13.0800

description: Enoyl reductase-like protein; Leishmania donovani (HU3 strain)
DOI: 10.17632/c2r7cmzf36.1
title: LDHU3_13.0920

description: Protein of unknown function - conserved; Leishmania donovani (HU3 strain)
DOI: 10.17632/f8ytb6jbct.1
title: LDHU3_13.0900

description: Hypothetical protein - conserved; Leishmania donovani (HU3 strain)
DOI: 10.17632/xx7gd694w4.1
title: LDHU3_13.0910

description: Succinate dehydrogenase assembly factor 3 | SDHAF3; Leishmania donovani (HU3 strain)
DOI: 10.17632/hvb2gxv2zx.1
title: If these walls could talk: investigating bottlenose dolphin occupancy and range in fiord ecosystems using passive acoustic monitoring and visual surveys

description: Data include daily acoustic detections in 6 fiords within the Fiordland (Te Moana o Atawhenua) Marine Area collected between February 2022 and November 2023.
DOI: 10.5281/zenodo.12790226
title: Unravelling Plankton Adaptation in Global Oceans through the Analysis of Lipidomes

description: This file contains all the data relevant to the manuscript titled “Unravelling Plankton Adaptation in Global Oceans through the Analysis of Lipidomes,” as well as all the code used to generate the data and the figures presented in the manuscript.
description: Microbial responses to environmental changes are well-studied in laboratory cultures, but in-situ adaptations of plankton lipidomes remain less understood. Building upon a global lipidomic study showing temperature-driven lipid unsaturation regulation in marine plankton, we expanded the analysis spatially and methodologically to investigate the in-situ adaptations of marine plankton. Through weighted correlation network analysis of 3,164 lipid species from 930 samples, we identified sixteen structurally distinct lipid clusters co-occurred across diverse oceanographic conditions. The highest lipid diversity was observed in the polar oceans, where plankton employs chain shortening for cold acclimation. Conversely, in the surface of tropical and subtropical oceans, plankton showed enrichment in non-phosphorus lipids, likely responding to warm temperature, with potential implications for the elemental stoichiometry of the biological pump. In the subsurface of these regions, highly unsaturated lipids were enriched, suggesting phytoplankton adaptation to low light and contributing unsaturated fatty acids to tropical and subtropical ocean food webs.
DOI: 10.5281/zenodo.12790227
title: Unravelling Plankton Adaptation in Global Oceans through the Analysis of Lipidomes

description: This file contains all the data relevant to the manuscript titled “Unravelling Plankton Adaptation in Global Oceans through the Analysis of Lipidomes,” as well as all the code used to generate the data and the figures presented in the manuscript.
description: A recent global survey of planktonic lipids showed a fundamental temperature-mediated regulation of lipid unsaturation in the global oceans [Holm H, et al. (2022) Science 376:1487–1491]. We expand the analysis of this dataset, both spatially and methodologically, to examine diverse environmental stressors across the ocean. Utilizing weighted correlation network analysis, we analyzed 3,164 lipid features in the dataset comprising 930 samples of suspended particulate matter, taken across a broad range of oceanographic conditions and water depths up to 600 meters. A total of 16 lipid clusters being co-expressed across diverse environments were identified. This analysis reveals universal relationships between environmental factors and the lipidome of the planktonic community. The largest lipid cluster, comprising 481 lipid features, including glycerolipids with polyunsaturated fatty acids, exhibited a significant enrichment in polar oceans, suggesting the highest lipid diversity in these ocean regions. Remarkably, marine plankton in these regions employ both desaturation and chain shortening for cold acclimation. Additionally, one lipid cluster strongly linked to the plankton residing in the surface of tropical and subtropical oceans was enriched with non-phosphorus lipids. We suggest this adaptive response enables the plankton to cope with phosphorous scarcity and heat stress. Notably, in the subsurface of these regions, a co-expressed cluster of highly unsaturated lipids is consistent with an enhanced production of polyunsaturated fatty acids by phytoplankton, possibly for low light adaptation. This adaptation is important as it may represent a source of essential fatty acids below the warm sea surface where such vital compounds may be diminished in the warmer future.
description: We thank everyone involved in creating and curating the dataset utilized in this study.
DOI: 10.5281/zenodo.14699653
title: Unravelling Plankton Adaptation in Global Oceans through the Analysis of Lipidomes

description: This file contains all the data relevant to the manuscript titled “Unravelling Plankton Adaptation in Global Oceans through the Analysis of Lipidomes,” as well as all the code used to generate the data and the figures presented in the manuscript.
description: Microbial responses to environmental changes are well-studied in laboratory cultures, but in-situ adaptations of plankton lipidomes remain less understood. Building upon a global lipidomic study showing temperature-driven lipid unsaturation regulation in marine plankton, we expanded the analysis spatially and methodologically to investigate the in-situ adaptations of marine plankton. Through weighted correlation network analysis of 3,164 lipid species from 930 samples, we identified sixteen structurally distinct lipid clusters co-occurred across diverse oceanographic conditions. The highest lipid diversity was observed in the polar oceans, where plankton employs chain shortening for cold acclimation. Conversely, in the surface of tropical and subtropical oceans, plankton showed enrichment in non-phosphorus lipids, likely responding to warm temperature, with potential implications for the elemental stoichiometry of the biological pump. In the subsurface of these regions, highly unsaturated lipids were enriched, suggesting phytoplankton adaptation to low light and contributing unsaturated fatty acids to tropical and subtropical ocean food webs.
DOI: 10.17632/5sfwx969fr.1
title: LDHU3_13.0860

description: Protein kinase; Leishmania donovani (HU3 strain)
DOI: 10.17632/nfnf4v7h67.1
title: LDHU3_19.0090

description: Protein of unknown function - conserved; Leishmania donovani (HU3 strain)
DOI: 10.17632/rtf5d2v9rm.2
title: Recognition of Damage Types of gray-brick Ancient Buildings Based on Machine Learning——Taking the Macau World Heritage Buffer Zone as an Example(Training set for machine learning)

description: As a result of environmental and human influences, several types of surface deterioration emerge on historic buildings, resulting in a decline in the quality of these structures and even threats to their safety. In the conventional approach, assessing the surface damage on a structure involves the time-consuming and labor-intensive judgment and evaluation of trained professionals. In this study, it is suggested that the YOLOv4 machine learning model be used to automatically find five types of damage to historical brick buildings. This would make the job go more quickly. This study uses the blue brick wall buildings in the buffer zone of the global cultural heritage in Macau as an example. 1355 photographs were taken on-site of the blue brick walls, and the six most common types of damage were identified. By slicing and labeling the photos, a training set of 1000 images was created, and through 200-generation model training, the model can accurately identify and effectively identify the damage state of the blue bricks and enhance the quality judgment and evaluation of the exterior walls of historical buildings. Experiments allow us to reach the following conclusions: (1) The damage to the blue-brick ancient buildings in Macau is affected by the subtropical maritime climate. Missing paint, stains, and cracks are the main contributors to brick wall damage. (2) Ma-chine learning can help determine the type of damage to old blue-brick buildings, which is useful for managing and protecting historical buildings. (3) The model in this study can identify five types of damage: missing, cracking, plant or microbial erosion, yellowing, and pollution on the exterior walls of ancient blue-brick buildings. It is helpful to accurately identify and evaluate the damaged con-dition of the brick wall and formulate corresponding protection schemes.
DOI: 10.17632/vd3x5tv4hw.1
title: Large et al. Near steady denudation rates during the late Pleistocene in the tropics

description: All data presented in article Large et al. "Near steady denudation rates during the late Pleistocene in the tropics" submitted to the Journal of Geophysical Research Earth Surface. The data is under the form of one excel document with each sheet corresponding to a table. See published text for additional explanation. For any question regarding the data, please contact Etienne Large at Etienne.large@univ-lorraine.fr or Etienne.lrg@gmail.com
DOI: 10.17632/rtf5d2v9rm.1
title: Recognition of Damage Types of Blue-brick Ancient Buildings Based on Machine Learning——Taking the Macau World Cultural Heritage Buffer Zone as an Example(Training set for machine learning)

description: As a result of environmental and human influences, several types of surface deterioration emerge on historic buildings, resulting in a decline in the quality of these structures and even threats to their safety. In the conventional approach, assessing the surface damage on a structure involves the time-consuming and labor-intensive judgment and evaluation of trained professionals. In this study, it is suggested that the YOLOv4 machine learning model be used to automatically find five types of damage to historical brick buildings. This would make the job go more quickly. This study uses the blue brick wall buildings in the buffer zone of the global cultural heritage in Macau as an example. 1355 photographs were taken on-site of the blue brick walls, and the six most common types of damage were identified. By slicing and labeling the photos, a training set of 1000 images was created, and through 200-generation model training, the model can accurately identify and effectively identify the damage state of the blue bricks and enhance the quality judgment and evaluation of the exterior walls of historical buildings. Experiments allow us to reach the following conclusions: (1) The damage to the blue-brick ancient buildings in Macau is affected by the subtropical maritime climate. Missing paint, stains, and cracks are the main contributors to brick wall damage. (2) Ma-chine learning can help determine the type of damage to old blue-brick buildings, which is useful for managing and protecting historical buildings. (3) The model in this study can identify five types of damage: missing, cracking, plant or microbial erosion, yellowing, and pollution on the exterior walls of ancient blue-brick buildings. It is helpful to accurately identify and evaluate the damaged con-dition of the brick wall and formulate corresponding protection schemes.
DOI: 10.17632/rtf5d2v9rm.3
title: Recognition of Damage Types of gray-brick Ancient Buildings Based on Machine Learning——Taking the Macau World Heritage Buffer Zone as an Example(Training set for machine learning)

description: As a result of environmental and human influences, several types of surface deterioration emerge on historic buildings, resulting in a decline in the quality of these structures and even threats to their safety. In the conventional approach, assessing the surface damage on a structure involves the time-consuming and labor-intensive judgment and evaluation of trained professionals. In this study, it is suggested that the YOLOv4 machine learning model be used to automatically find five types of damage to historical gray-brick buildings. This would make the job go more quickly. This study uses the gray-brick wall buildings in the buffer zone of the global cultural heritage in Macau as an example. In total, 1355 photographs were taken on-site of the gray-brick walls, and the five most common types of damage were identified. By slicing and labeling the photos, a training set of 1000 images was created, and through 200-generation model training, the model can accurately identify and effectively identify the damage state of the gray bricks and enhance the quality judgment and evaluation of the exterior walls of historical buildings. Experiments allow us to reach the following conclusions: (1) The damage to the gray-brick ancient buildings in Macau is affected by the subtropical maritime climate. Missing paint, stains, and cracks are the main contributors to gray-brick wall damage. (2) Machine learning can help determine the type of damage to old gray-brick buildings, which is useful for managing and protecting historical buildings. (3) The model in this study can identify five types of damage: missing, cracking, plant or microbial erosion, yellowing, and pollution on the exterior walls of ancient gray-brick buildings. It is helpful to accurately identify and evaluate the damaged condition of the gray-brick wall and formulate corresponding protection schemes.
DOI: 10.17632/zbfxf8kwvn.1
title: Dataset Advancement: Glycan Composition and Peptide Mass Fingerprinting of the Native Torpedo californica Nicotinic Acetylcholine Receptor after a Multi-Step Sequential Purification Method

description: The study described in this dataset focuses on the characterization of the nicotinic acetylcholine receptor (nAChR), a member of the Cys-loop pentameric ligand-gated ion channels that play critical roles in organismal function. Our research efforts have resulted in the successful production of a highly pure nAChR, which has allowed for more robust studies to be conducted, including high-throughput crystallization experiments. Using advanced technologies such as Nano Lc MS/MS and MALDI ToF/ToF, we have identified and extensively characterized each nAChR subunit, achieving a 100% identity. Furthermore, we have investigated the N-linked glycans in the Torpedo californica-nAChR (Tc-nAChR) subunits. By digesting the Tc-nAChR subunits with PNGase F and analyzing the released glycans with MALDI-ToF, we identified the presence of high-mannose N-glycan in all native Tc-nAChR subunits. Specifically, we observed the oligommanose population Man8-9GlcNac2 with peaks at m/z 1742 and 1904 ([M + Na]+ ions). Overall, this study emphasizes the importance of continued research efforts aimed at understanding the complex biology of the Cys-loop pentameric ligand-gated ion channels and their involvement in organismal function and disease. The insights gained from such studies could have far-reaching implications for the development of new therapeutic strategies to combat a wide range of health issues.
DOI: 10.17632/x3kxjddv9d.1
title: The influence of parasite load on transcriptional activity and morphology of a cestode and its ant intermediate host

description: Parasites with complex life cycles are known to induce phenotypic changes in their intermediate hosts to increase transmission to the final host. The magnitude of these changes could increase with the number of parasites, which would be beneficial to co-infecting parasites. Yet, adverse effects of high parasite load (i.e., many parasites in a single host) might stress both hosts and parasites (e.g., through an increased immune response). We investigated the consequences of parasite load on the transcriptional activity and morphology of the cestode Anomotaenia brevis and its intermediate host, the ant Temnothorax nylanderi. We demonstrated that many differentially expressed host genes shifted with parasite load, and their functions indicate a stronger immune response and fight against oxidative stress in heavily infected hosts. The expression of other host genes responded to infection in an all-or-nothing manner, as did the morphology of the host workers. However, the cestodes became smaller when they competed with other parasites for resources from a single host. Their expression profile further indicated shifts in host immune avoidance, starvation resistance and vesicle-mediated transport. In summary, our study reveals clear consequences of parasite load and highlights specific processes and traits affected by this.
DOI: 10.17632/p9rsyr9r4x.1
title: Spatial constraints in cellular automata-based urban growth models: a systematic comparison of classifiers and input urban maps

description: Data and code repository for associated publication of same title.
Information on the description of the datasets and the main code is presented in the README file.
DOI: 10.17632/p9rsyr9r4x.2
title: Spatial constraints in cellular automata-based urban growth models: a systematic comparison of classifiers and input urban maps

description: Data and code repository for associated publication of same title.
Information on the description of the datasets and the main code is presented in the README file.
DOI: 10.17632/9njx9rm5yy.1
title: Underwater coastal protection monitoring from UAV dataset

description: The data covers monitoring from 2016 to 2021. Three photogrammetric surveys were conducted in the study area (Rowy, Poland) using an unmanned aerial vehicle (UAV), capturing JPG images from which point clouds were derived. The dataset comprises both raw images and processed, cropped orthophotos in TIF format, suitable for use in GIS systems.
DOI: 10.17632/n64y6pwfng.1
title: LINF_350040100

description: acyl transferase-like protein
Leishmania infantum (strain JPCM5)
DOI: 10.17632/86k94wfzfc.1
title: Body mass of rufous horneros in Brasília, Brazil

description: Body mass measurements taken from adult birds between 2013 and 2015. These measurements were obtained utilizing a dynamometer (Pesola 100 g) at the Darcy Ribeiro Campus of the Universidade de Brasília, Brazil. The datasheet includes bird identity code, sex (F: female, M: male), date (DD/MM/YYYY), longitude (long, in decimal degrees), latitude (lat, in decimal degrees), and body mass (in grams). Geographic coordinates specify the approximate location of the Darcy Ribeiro Campus at the Universidade de Brasília.
DOI: 10.17632/vb6bd463yk.1
title: LINF_350040300

description: mitoribosomal protein mS26
Leishmania infantum (strain JPCM5)
DOI: 10.17632/x2nh7bvr76.1
title: Task allocation Dinoponera quadriceps

description: We are providing the Gross Data (Excel spreadsheet) used in the analysis, in addition to the codes/script used in R language.
DOI: 10.17632/b6n3sk9gyf.1
title: Table II. Characteristics of the overall study population

description: Table II. Characteristics of the overall study population of cutaneous melanoma NCDB
DOI: 10.17632/hshk3vstmg.1
title: Table I. Comparison of Black versus white time to surgical intervention

description: Comparison of Black versus white time to surgical intervention for cutaneous melanoma.
DOI: 10.17632/f8fhyk9ff6.1
title: Dengue_diabetes_datases

description: It's a database regarding a dengue outbreak that occurred in São José do Rio Preto, SP, Brazil, in 2019, containing anonymized demographic and clinical findings of confirmed dengue cases.
DOI: 10.17632/ch4tdcn5c8.1
title: The accuracy of a new device using mixed reality surgical navigation (MRSN) with UCRT frame

description: 1. Time of 3D Model Reconstruction &lt;20s
Computational data from CT scanned bones (Dicom sequence files) were imported into the Mimmics software to be created into a visualized 3D digital model file in .stl format in less than 20 seconds.

2. Loading Time of a 3D Model &lt;10s
This system loads the required time to visualize the 3D numeric model. After booting the system software, the process can be completed in 10 seconds by choosing to start with the finished visualized 3D digital model created, to display it in the software, and to complete the automatic registration of the 3D digital model with the real skeleton.

3. Clinical positioning accuracy &lt;1 mm
The deviation was defined as the difference between the planned screw pathway, based on a visualized 3D digital model or an intraoperative fluroscoply, and the actual positioning of the screw pathway.

4. 3D Reconstruction/Intelligent Registry Accuracy &lt;0.5 mm
The 3D model of the system’s reconstitution differed in shape and volume from that of the real skeleton, i.e. the reconstitution accuracy of the 3D model was ±0.5 mm. When automated intelligent registration was completed, the spatial position of the 3D model was displayed in real time as the difference between the spatial position of the actual skeleton and the spatial position of the 3D model, i.e. the 3D model’s intelligent registration accuracy was ±0.5 mm.
DOI: 10.17632/9kxd7m4twn.1
title: Dupilumab alleviates pruritus regardless of skin improvement in adults with atopic dermatitis: a cohort study

description: Supplementary materials of "Dupilumab alleviates pruritus regardless of skin improvement in adults with atopic dermatitis: a cohort study"
DOI: 10.17632/ctz6jmkyhw.1
title: The effect of visa types on international tourism

description: This database provides data to estimate a structural gravity model for worldwide tourism movements, including domestic flows, from 194 origin countries to 163 destinations for the period 2016 to 2021. Moreover, it includes bilateral visa requirements
DOI: 10.17632/fcwtc9mytw.1
title: LINF_350041600

description: iron-sulfur cluster assembly protein | IscU
Leishmania infantum (strain JPCM5)
DOI: 10.17632/f7jgn6b9mw.1
title: MCDFM DATA

description: Case related data: flume experiment and survey of Tianchi volcano area in Changbai Mountain, and related original simulation data.
Paper data: An integrated hydrodynamic model for multi-component debris flow a case study of lahar in Changbaishan-Tianchi Volcano.
DOI: 10.17632/rg8y7pyyzz.1
title: data in brief_γ-Tocotrienol Inhibits Cervical Cancer HeLa Cells Growth through Regulating the PI3K/AKT/mTOR Signaling Pathway

description: The file is a Data in Brief used by Xu et al study forγ-Tocotrienol Inhibits Cervical Cancer HeLa Cells Growth through Regulating the PI3K/AKT/mTOR Signaling Pathway in vitro. The data showed that γ-T3 (30-60 μM, especially at 45 μM) treatment significantly inhibited HeLa cellular proliferation, and its IC50 was 37.40 ± 5.70 µM at 48 hours. It induced apoptosis and increased the proportion of cells in G0/G1 phase and decreased the proportion at S phase in HeLa cells. The treatment decreased the levels of both phosphorylated and non-phosphorylated (+/-p) mTOR, upstream regulatory factors of PI3K, (+/-p) AKT, downstream regulatory factors of (+/-p) p70S6K, (+/-p) 4E-BP1 and targeted genes of Cyclin D1 and c-Myc related to HeLa cell proliferation and apoptosis. These eﬀects of γ-T3 on the HeLa cells were similar to the actions of Wortmannin (WM), a known blocker of the PI3K/AKT/mTOR signaling pathway. Furthermore, the combination of γ-T3 and WM displayed a strong synergistic effect. These results suggest that γ-T3 could inhibit cell growth by down-regulating the PI3K/AKT/mTOR signaling pathway in human cervical cancer HeLa cells.
DOI: 10.17632/rny9npsn49.1
title: LINF_350041800

description: hypothetical protein - conserved
Leishmania infantum (strain JPCM5)