cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23552096
title: The characteristic of the complete chloroplast genome of <i>Lithocarpus konishii</i> (Fagaceae), a rare and endemic species in South China

description: <i>Lithocarpus konishii</i>, a rare species endemic to islands in South China, was evaluated as a vulnerable species (VU) by the ‘China Species Red List.’ Here, we first presented the complete chloroplast genome sequence of <i>L. konishii.</i> The chloroplast genome was 161,059 bp in length with 36.76% GC content, containing a small single-copy region (SSC, 18,967 bp), a large single-copy region (LSC, 90,250 bp), and a pair of inverted repeats (IRs, 25,921 bp each). A total of 139 genes were predicted, including 87 protein-coding genes (CDS), 8 rRNAs, and 44 tRNAs. Based on the concatenated shared unique CDS sequence dataset, maximum-likelihood and Bayesian inference methods were used to build the phylogenetic trees of 18 species from the Fagaceae family. Results indicated that <i>L. konishii</i> is closely related to <i>L. longnux</i> and <i>L. pachyphyllus</i> var. <i>fruticosus</i>, and forms a monophyly of the subfamily Castaneoideae with <i>Castanopsis</i> and <i>Castanea</i>. This study provides a theoretical basis for the conservation genomics of this endangered plant.
DOI: 10.6084/m9.figshare.23552096.v1
title: The characteristic of the complete chloroplast genome of <i>Lithocarpus konishii</i> (Fagaceae), a rare and endemic species in South China

description: <i>Lithocarpus konishii</i>, a rare species endemic to islands in South China, was evaluated as a vulnerable species (VU) by the ‘China Species Red List.’ Here, we first presented the complete chloroplast genome sequence of <i>L. konishii.</i> The chloroplast genome was 161,059 bp in length with 36.76% GC content, containing a small single-copy region (SSC, 18,967 bp), a large single-copy region (LSC, 90,250 bp), and a pair of inverted repeats (IRs, 25,921 bp each). A total of 139 genes were predicted, including 87 protein-coding genes (CDS), 8 rRNAs, and 44 tRNAs. Based on the concatenated shared unique CDS sequence dataset, maximum-likelihood and Bayesian inference methods were used to build the phylogenetic trees of 18 species from the Fagaceae family. Results indicated that <i>L. konishii</i> is closely related to <i>L. longnux</i> and <i>L. pachyphyllus</i> var. <i>fruticosus</i>, and forms a monophyly of the subfamily Castaneoideae with <i>Castanopsis</i> and <i>Castanea</i>. This study provides a theoretical basis for the conservation genomics of this endangered plant.
DOI: 10.5281/zenodo.8077195
title: MegaWeeds dataset

description: The MegaWeeds dataset consists of seven existing datasets: - WeedCrop dataset; Sudars, K., Jasko, J., Namatevs, I., Ozola, L., & Badaukis, N. (2020). Dataset of annotated food crops and weed images for robotic computer vision control. <em>Data in Brief</em>, <em>31</em>, 105833. https://doi.org/https://doi.org/10.1016/j.dib.2020.105833 - Chicory dataset; Gallo, I., Rehman, A. U., Dehkord, R. H., Landro, N., La Grassa, R., & Boschetti, M. (2022). <em>Weed detection by UAV 416a Image Dataset</em>. https://universe.roboflow.com/chicory-crop-weeds-5m7vo/weed-detection-by-uav-416a/dataset/1 - Sesame dataset; Utsav, P., Raviraj, P., & Rayja, M. (2020). <em>crop and weed detection data with bounding boxes</em>. https://www.kaggle.com/datasets/ravirajsinh45/crop-and-weed-detection-data-with-bounding-boxes - Sugar beet dataset; Wangyongkun. (2020). <em>sugarbeetsAndweeds</em>. https://www.kaggle.com/datasets/wangyongkun/sugarbeetsandweeds - Weed-Detection-v2; Tandon, K. (2021, June). <em>Weed_Detection_v2</em>. https://www.kaggle.com/datasets/kushagratandon12/weed-detection-v2 - Maize dataset; Correa, J. M. L., D. Andújar, M. Todeschini, J. Karouta, JM Begochea, & Ribeiro A. (2021). <em>WeedMaize</em>. Zenodo. https://doi.org/10.5281/ZENODO.5106795 - CottonWeedDet12 dataset; Dang, F., Chen, D., Lu, Y., & Li, Z. (2023). YOLOWeeds: A novel benchmark of YOLO object detectors for multi-class weed detection in cotton production systems. <em>Computers and Electronics in Agriculture</em>, <em>205</em>, 107655. https://doi.org/https://doi.org/10.1016/j.compag.2023.107655 All the datasets contain open-field images from crops and weeds with annotations. The annotation files were converted to text files so it can be used in the YOLO model. All the datasets were combined into one big dataset with in total 19,317 images. The dataset is split into a training and validation set.
DOI: 10.5281/zenodo.8077194
title: MegaWeeds dataset

description: The MegaWeeds dataset consists of seven existing datasets: - WeedCrop dataset; Sudars, K., Jasko, J., Namatevs, I., Ozola, L., & Badaukis, N. (2020). Dataset of annotated food crops and weed images for robotic computer vision control. <em>Data in Brief</em>, <em>31</em>, 105833. https://doi.org/https://doi.org/10.1016/j.dib.2020.105833 - Chicory dataset; Gallo, I., Rehman, A. U., Dehkord, R. H., Landro, N., La Grassa, R., & Boschetti, M. (2022). <em>Weed detection by UAV 416a Image Dataset</em>. https://universe.roboflow.com/chicory-crop-weeds-5m7vo/weed-detection-by-uav-416a/dataset/1 - Sesame dataset; Utsav, P., Raviraj, P., & Rayja, M. (2020). <em>crop and weed detection data with bounding boxes</em>. https://www.kaggle.com/datasets/ravirajsinh45/crop-and-weed-detection-data-with-bounding-boxes - Sugar beet dataset; Wangyongkun. (2020). <em>sugarbeetsAndweeds</em>. https://www.kaggle.com/datasets/wangyongkun/sugarbeetsandweeds - Weed-Detection-v2; Tandon, K. (2021, June). <em>Weed_Detection_v2</em>. https://www.kaggle.com/datasets/kushagratandon12/weed-detection-v2 - Maize dataset; Correa, J. M. L., D. Andújar, M. Todeschini, J. Karouta, JM Begochea, & Ribeiro A. (2021). <em>WeedMaize</em>. Zenodo. https://doi.org/10.5281/ZENODO.5106795 - CottonWeedDet12 dataset; Dang, F., Chen, D., Lu, Y., & Li, Z. (2023). YOLOWeeds: A novel benchmark of YOLO object detectors for multi-class weed detection in cotton production systems. <em>Computers and Electronics in Agriculture</em>, <em>205</em>, 107655. https://doi.org/https://doi.org/10.1016/j.compag.2023.107655 All the datasets contain open-field images from crops and weeds with annotations. The annotation files were converted to text files so it can be used in the YOLO model. All the datasets were combined into one big dataset with in total 19,317 images. The dataset is split into a training and validation set.
DOI: 10.17632/dwn7rb8ghf.1
title: Automatic identification of seismic building structure types using unmanned aerial vehicle oblique photography and deep learning

description: This is the sample data obtained from network crawling and source code  in the "Automatic identification of seismic building structure types using unmanned aerial vehicle oblique photography and deep learning", which is used for the reproduction and verification of the experiment. Including sample images and TFRecord data. Code includes data collection, facade extraction, PKAB_ net。
DOI: 10.17632/dwn7rb8ghf.2
title: Automatic identification of building structure types using unmanned aerial vehicle oblique images and deep learning considering facade prior knowledge

description: This is the sample data obtained from network crawling and source code  in the "Automatic identification of building structure types using unmanned
aerial vehicle oblique images and deep learning considering facade prior knowledge", which is used for the reproduction and verification of the experiment. Including sample images and TFRecord data. Code includes data collection, facade extraction, PKAB_ net。
DOI: 10.5281/zenodo.8099632
title: Raw NMR data for the article "Photochemical [2+2] Cycloaddition of Alkynyl Boronates"

description: Raw NMR data for the article "Photochemical [2+2] Cycloaddition of Alkynyl Boronates" published in Chemistry A European Journal, DOI: https://doi.org/10.1002/chem.202301650 The number of the folders either correspond to compounds numbers in the article or the name of the folder is self-describing. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.
DOI: 10.5281/zenodo.8099631
title: Raw NMR data for the article "Photochemical [2+2] Cycloaddition of Alkynyl Boronates"

description: Raw NMR data for the article "Photochemical [2+2] Cycloaddition of Alkynyl Boronates" published in Chemistry A European Journal, DOI: https://doi.org/10.1002/chem.202301650 The number of the folders either correspond to compounds numbers in the article or the name of the folder is self-describing. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.
DOI: 10.34740/kaggle/dsv/6070580
title: IPL_2023_data_by_rahman
DOI: 10.6084/m9.figshare.23617059
title: R code

description: R code
DOI: 10.6084/m9.figshare.23617080
title: Research Findings

description: The data incorporated are the spatial finding of the research based on three models, 1. Frequency ratio, 2. Information Value and 3. Shannon Entropy models.
DOI: 10.6084/m9.figshare.23617080.v1
title: Research Findings

description: The data incorporated are the spatial finding of the research based on three models, 1. Frequency ratio, 2. Information Value and 3. Shannon Entropy models.
DOI: 10.4121/bac024f1-6c2e-4a09-bf0f-be78b6bbe21c.v1
title: Scripts and data for "Historical shifts in seasonality and timing of extreme precipitation"

description: This dataset contains the python scripts and NetCDF data for the analyses and to recreate the figures of the manuscript: "Historical shifts in seasonality and timing of extreme precipitation" by Gaby Gründemann, Enrico Zorzetto, Nick van de Giesen, and Ruud van der Ent
DOI: 10.5281/zenodo.7893940
title: Molybdenum isotope signatures of forearc serpentinites: Origin and contribution to the subduction zone Mo cycle

description: Table 1. Mo contents and Sr-Pb-Mo isotope compositions of the serpentinites and metabasites from the Mariana forearc mud volcanoes.<br> Table 2. Parameters for the mixing calculations. Supplementary Tables:<br> Table S1. Sampling locations and descriptions of the samples from the Mariana forearc mud volcanoes.<br> Table S2. Analytical major elements, trace elements and Mo isotopes of standard samples.<br> Table S3. Major and trace element compositions of lavas from Mariana forearc mud volcanoes.
DOI: 10.5281/zenodo.7893941
title: Mg isotope evidence for carbonate recycling into sub-arc mantle beneath the Ryukyu subduction zone

description: Fig. S1. SiO2 versus 87Sr/86Sr plots (a) and SiO2 versus 143Nd/144Nd plots (b) of the studied samples and literature data. The symbols and cited literature are the same as in Fig. 1. These plots indicate that crustal assimilation has a minor influence on the magmatic evolution of basalts from MOT, SOT, and NTVZ, but is a major factor for andesites from KST and dacite from SOT.<br> Fig. S2. MgO versus other oxides diagrams for the studied samples and cited literature data. The symbols and cited literature are the same as in Fig. 1.<br> Fig. S3. An enlarged figure shows the mixing modeling of the depleted mantle and subducted enriched components. Mixing curves are marked in 10% increments. Subducted enriched components consist of altered oceanic crust (A) and dolomite-rich carbonate sediment (D), where the proportion of dolostone sediment is 20-40%. Three mixing lines between the depleted mantle and low δ26Mg carbonate end members (calcite, magnesite, and dolomite) are shown, which suggests that the injection of magnesite and calcite in the mantle is not the main factor to produce low-δ26Mg volcanic rocks. The isotopic ratios and element concentrations of all end-members can be found in Table 2. <br> Table 1. Mg isotopic compositions of volcanic rocks from Ryukyu subduction zone.<br> Table 2. Parameters for the mixing calculations.<br> Table S1. Major, trace elements and Sr-Nd isotopic compositions of volcanic rocks from Ryukyu subduction zone.
DOI: 10.5281/zenodo.8107087
title: Molybdenum isotope signatures of forearc serpentinites: Origin and contribution to the subduction zone Mo cycle

description: Table 1. Mo contents and Sr-Pb-Mo isotope compositions of the serpentinites and metabasites from the Mariana forearc mud volcanoes.<br> Table 2. Parameters for the mixing calculations. Supplementary Tables:<br> Table S1. Sampling locations and descriptions of the samples from the Mariana forearc mud volcanoes.<br> Table S2. Analytical major elements, trace elements and Mo isotopes of standard samples.<br> Table S3. Major and trace element compositions of lavas from Mariana forearc mud volcanoes.
DOI: 10.25345/c5697079m
title: MassIVE MSV000092331 - Proteomics Analysis of the UMK2 Mutation in Arabidopsis thaliana seeds
title: We compared the proteome of dry as well as germinating seeds of Arabidopsis thaliana wild type Col-0 with the respective proteomes from an umk2 (AT4G25280) frameshift mutant. Germinating seeds were incubated for 48 hours in 1/2-MS medium in Petri dishes at 4 degree Celsius followed by 24 hours of a phytochamber under long-day conditions. Protein extraction, digestion by SP3 workflow, and LC-IMS-MS/MS analysis as described in https://doi.org/10.1038/s41477-022-01308-6.
DOI: 10.6084/m9.figshare.23258981.v1
title: Raw data - WB.zip

description: Original WB images and data of manuscript <strong>TWIST1 Facilitates Pancreatic Cancer Progression by Translational Regulation of HK2 to Promote Cell Glycolysis, Invasion, and Metastasis</strong>
DOI: 10.5281/zenodo.8107144
title: Molybdenum isotope signatures of forearc serpentinites: Origin and contribution to the subduction zone Mo cycle

description: Table 1. Mo contents and Sr-Pb-Mo isotope compositions of the serpentinites and metabasites from the Mariana forearc mud volcanoes.<br> Table 2. Parameters for the mixing calculations. Supplementary Tables:<br> Table S1. Sampling locations and descriptions of the samples from the Mariana forearc mud volcanoes.<br> Table S2. Analytical major elements, trace elements and Mo isotopes of standard samples.<br> Table S3. Major and trace element compositions of lavas from Mariana forearc mud volcanoes.
DOI: 10.5281/zenodo.8107118
title: Analysis data of stream water drained from sub-catchments with different ranges of permafrost area percentage in the headwater region of the Heihe River

description: Here we provide the analysis data of stream water drained from sub-catchments with different ranges of permafrost area percentage in the headwater region of the Heihe River.
DOI: 10.5281/zenodo.8107117
title: Analysis data of stream water drained from sub-catchments with different ranges of permafrost area percentage in the headwater region of the Heihe River

description: Here we provide the analysis data of stream water drained from sub-catchments with different ranges of permafrost area percentage in the headwater region of the Heihe River.
DOI: 10.5281/zenodo.7848302
title: Supplementary Material for "Entropic barrier of water permeation through single-file channels"

description: Python code for a global activation energy (E<sub>a</sub>) fit to temperature dependent stopped-flow data (*.bka file): As shown in our manuscript, the accuracy of E<sub>a</sub> estimation from stopped-flow data is greatly increased by a global fit to the data. Thereby, the ensemble of curves of a sample at different temperatures is fitted globally using the analytical solution (<strong>Eqn. </strong><strong>10</strong>), instead of evaluating permeabilities for different temperatures individually and independently. In our python code, osmotic water flux measurements of a sample (mixture of vesicles with and without water channels) recorded at different temperatures are simultaneously fitted using <strong>Eqn. </strong><strong>7</strong>, <strong>Eqn. </strong><strong>10</strong>,<strong> Eqn. </strong><strong>11</strong> and <strong>Eqn. </strong><strong>14</strong>. Here, the only free fit parameter, which is evaluated for the different temperatures independently is coefficient <em>b</em> from <strong>Eqn. </strong><strong>7</strong>. The accuracy of the results increases with the span of the temperature values, number of performed measurements and a decreased empty vesicle fraction.
DOI: 10.5281/zenodo.7848301
title: Supplementary Material for "Entropic barrier of water permeation through single-file channels"

description: Python code for a global activation energy (E<sub>a</sub>) fit to temperature dependent stopped-flow data (*.bka file): As shown in our manuscript, the accuracy of E<sub>a</sub> estimation from stopped-flow data is greatly increased by a global fit to the data. Thereby, the ensemble of curves of a sample at different temperatures is fitted globally using the analytical solution (<strong>Eqn. </strong><strong>10</strong>), instead of evaluating permeabilities for different temperatures individually and independently. In our python code, osmotic water flux measurements of a sample (mixture of vesicles with and without water channels) recorded at different temperatures are simultaneously fitted using <strong>Eqn. </strong><strong>7</strong>, <strong>Eqn. </strong><strong>10</strong>,<strong> Eqn. </strong><strong>11</strong> and <strong>Eqn. </strong><strong>14</strong>. Here, the only free fit parameter, which is evaluated for the different temperatures independently is coefficient <em>b</em> from <strong>Eqn. </strong><strong>7</strong>. The accuracy of the results increases with the span of the temperature values, number of performed measurements and a decreased empty vesicle fraction.
DOI: 10.6084/m9.figshare.23617152
title: Raw data: Lateral and vertical patterns of the function and structure of nitrifying and denitrifying microbial communities in rivers across China

description: Raw data for “Lateral and vertical patterns of the function and structure of nitrifying and denitrifying microbial communities in rivers across China”.
DOI: 10.48677/ee871d1d-aad0-4c85-89b7-076ec62265c0
title: ALS DTM CRS3035RES50000mN2650000E4500000 Höhenraster 1m Stichtag 15.09.2022

description: Das ALS DTM-Höhenraster gehört zur Produktgruppe "Digitales Geländehöhenmodell" (DGM). Das digitale Geländehöhenmodell (DGM) beschreibt die Erdoberfläche (natürlicher Boden, ohne Bewuchs) in Form von Punktmengen, die in einem regelmäßigen Gitter von 1m angeordnet und in Lage und Höhe in den europäischen Referenzsystemen georeferenziert sind. Das ALS DTM Höhenraster wurde mit Airborne Laserscanning Technologien aufgenommen. Das ALS DTM Höhenraster ist ein Kooperationsprodukt der österreichischen behördlichen Geodatenprovider des Bundes und der Länder. Dies ist eine von insgesamt 55 Kacheln, welche zusammen das Gebiet Österreich abdecken.
DOI: 10.48677/c2dcb171-c23e-4bf0-9019-21ac018e4b9a
title: ALS DTM CRS3035RES50000mN2650000E4550000 Höhenraster 1m Stichtag 15.09.2022

description: Das ALS DTM-Höhenraster gehört zur Produktgruppe "Digitales Geländehöhenmodell" (DGM). Das digitale Geländehöhenmodell (DGM) beschreibt die Erdoberfläche (natürlicher Boden, ohne Bewuchs) in Form von Punktmengen, die in einem regelmäßigen Gitter von 1m angeordnet und in Lage und Höhe in den europäischen Referenzsystemen georeferenziert sind. Das ALS DTM Höhenraster wurde mit Airborne Laserscanning Technologien aufgenommen. Das ALS DTM Höhenraster ist ein Kooperationsprodukt der österreichischen behördlichen Geodatenprovider des Bundes und der Länder. Dies ist eine von insgesamt 55 Kacheln, welche zusammen das Gebiet Österreich abdecken.
DOI: 10.5281/zenodo.8107209
title: Database of the mechanical properties of FRP composites subjected to different environmental effects

description: The database is established by collecting FRP aging test data from various published literature, with a uniform record format to ensure consistency. The database comprises two main categories: accelerated aging and natural aging. The recorded accelerated aging data were further sorted into five types: water immersion aging, alkaline solution aging, acidic solution aging, high-temperature aging, and ultraviolet radiation aging.
DOI: 10.5281/zenodo.8107208
title: Database of the mechanical properties of FRP composites subjected to different environmental effects

description: The database is established by collecting FRP aging test data from various published literature, with a uniform record format to ensure consistency. The database comprises two main categories: accelerated aging and natural aging. The recorded accelerated aging data were further sorted into five types: water immersion aging, alkaline solution aging, acidic solution aging, high-temperature aging, and ultraviolet radiation aging.
DOI: 10.48677/3563eb95-c95a-4ff2-b638-ab50023d938a
title: ALS DTM CRS3035RES50000mN2650000E4600000 Höhenraster 1m Stichtag 15.09.2022

description: Das ALS DTM-Höhenraster gehört zur Produktgruppe "Digitales Geländehöhenmodell" (DGM). Das digitale Geländehöhenmodell (DGM) beschreibt die Erdoberfläche (natürlicher Boden, ohne Bewuchs) in Form von Punktmengen, die in einem regelmäßigen Gitter von 1m angeordnet und in Lage und Höhe in den europäischen Referenzsystemen georeferenziert sind. Das ALS DTM Höhenraster wurde mit Airborne Laserscanning Technologien aufgenommen. Das ALS DTM Höhenraster ist ein Kooperationsprodukt der österreichischen behördlichen Geodatenprovider des Bundes und der Länder. Dies ist eine von insgesamt 55 Kacheln, welche zusammen das Gebiet Österreich abdecken.
DOI: 10.48677/bb4425d1-c3ef-444a-b122-8e1b5662b3ca
title: ALS DTM CRS3035RES50000mN2650000E4650000 Höhenraster 1m Stichtag 15.09.2022

description: Das ALS DTM-Höhenraster gehört zur Produktgruppe "Digitales Geländehöhenmodell" (DGM). Das digitale Geländehöhenmodell (DGM) beschreibt die Erdoberfläche (natürlicher Boden, ohne Bewuchs) in Form von Punktmengen, die in einem regelmäßigen Gitter von 1m angeordnet und in Lage und Höhe in den europäischen Referenzsystemen georeferenziert sind. Das ALS DTM Höhenraster wurde mit Airborne Laserscanning Technologien aufgenommen. Das ALS DTM Höhenraster ist ein Kooperationsprodukt der österreichischen behördlichen Geodatenprovider des Bundes und der Länder. Dies ist eine von insgesamt 55 Kacheln, welche zusammen das Gebiet Österreich abdecken.
DOI: 10.48677/92221751-e956-4255-a868-3687198f84e5
title: ALS DTM CRS3035RES50000mN2650000E4700000 Höhenraster 1m Stichtag 15.09.2022

description: Das ALS DTM-Höhenraster gehört zur Produktgruppe "Digitales Geländehöhenmodell" (DGM). Das digitale Geländehöhenmodell (DGM) beschreibt die Erdoberfläche (natürlicher Boden, ohne Bewuchs) in Form von Punktmengen, die in einem regelmäßigen Gitter von 1m angeordnet und in Lage und Höhe in den europäischen Referenzsystemen georeferenziert sind. Das ALS DTM Höhenraster wurde mit Airborne Laserscanning Technologien aufgenommen. Das ALS DTM Höhenraster ist ein Kooperationsprodukt der österreichischen behördlichen Geodatenprovider des Bundes und der Länder. Dies ist eine von insgesamt 55 Kacheln, welche zusammen das Gebiet Österreich abdecken.
DOI: 10.48677/9aec5845-1047-4658-936f-8b74f917c26e
title: ALS DTM CRS3035RES50000mN2650000E4750000 Höhenraster 1m Stichtag 15.09.2022

description: Das ALS DTM-Höhenraster gehört zur Produktgruppe "Digitales Geländehöhenmodell" (DGM). Das digitale Geländehöhenmodell (DGM) beschreibt die Erdoberfläche (natürlicher Boden, ohne Bewuchs) in Form von Punktmengen, die in einem regelmäßigen Gitter von 1m angeordnet und in Lage und Höhe in den europäischen Referenzsystemen georeferenziert sind. Das ALS DTM Höhenraster wurde mit Airborne Laserscanning Technologien aufgenommen. Das ALS DTM Höhenraster ist ein Kooperationsprodukt der österreichischen behördlichen Geodatenprovider des Bundes und der Länder. Dies ist eine von insgesamt 55 Kacheln, welche zusammen das Gebiet Österreich abdecken.
DOI: 10.6084/m9.figshare.23617200
title: <strong>Amino acids profiling in CKD</strong>

description: Supplementary material and source data for manuscript
DOI: 10.6084/m9.figshare.23617200.v1
title: <strong>Amino acids profiling in CKD</strong>

description: Supplementary material and source data for manuscript