cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25505/fiz.icsd.cc2g1l04
title: CSD 2265635: Experimental Crystal Structure Determination

description: Related Article: Guoliang Feng|2023|ICSD Communication|||
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.25505/fiz.icsd.cc2g1l15
title: CSD 2265636: Experimental Crystal Structure Determination

description: Related Article: Guoliang Feng|2023|ICSD Communication|||
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.25505/fiz.icsd.cc2g1l26
title: CSD 2265637: Experimental Crystal Structure Determination

description: Related Article: Guoliang Feng|2023|ICSD Communication|||
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.7958259
title: CTU-SME-11: a labeled dataset with real benign and malicious network traffic mimicking a small medium-size enterprise environment

description: As technology advances, the number and complexity of cyber-attacks increase, forcing defense techniques to be updated and improved. To help develop effective tools for detecting security threats it is essential to have reliable and representative security datasets. Many existing security datasets have limitations that make them unsuitable for research, including lack of labels, unbalanced traffic, and outdated threats. CTU-SME-11 is a labeled network dataset designed to address the limitations of previous datasets. The dataset was captured in a real network that mimics a small-medium enterprise setting. Raw network traffic (packets) was captured from 11 devices using tcpdump for a duration of 7 days, from 20th to 26th of February, 2023 in Prague, Czech Republic. The devices were chosen based on the enterprise setting and consists of IoT, desktop and mobile devices, both bare metal and virtualized. The devices were infected with malware or exposed to Internet attacks, and factory reset to restore benign behavior. The raw data was processed to generate network flows (Zeek logs) which were analyzed and labeled. The dataset contains two types of levels, a high level label and a descriptive label, which were put by experts. The former can take three values, benign, malicious or background. The latter contains detailed information about the specific behavior observed in the network flows. The dataset contains 99 million labeled network flows. The overall compressed size of the dataset is 80GB and the uncompressed size is 170GB.
DOI: 10.5281/zenodo.7958258
title: CTU-SME-11: a labeled dataset with real benign and malicious network traffic mimicking a small medium-size enterprise environment

description: As technology advances, the number and complexity of cyber-attacks increase, forcing defense techniques to be updated and improved. To help develop effective tools for detecting security threats it is essential to have reliable and representative security datasets. Many existing security datasets have limitations that make them unsuitable for research, including lack of labels, unbalanced traffic, and outdated threats. CTU-SME-11 is a labeled network dataset designed to address the limitations of previous datasets. The dataset was captured in a real network that mimics a small-medium enterprise setting. Raw network traffic (packets) was captured from 11 devices using tcpdump for a duration of 7 days, from 20th to 26th of February, 2023 in Prague, Czech Republic. The devices were chosen based on the enterprise setting and consists of IoT, desktop and mobile devices, both bare metal and virtualized. The devices were infected with malware or exposed to Internet attacks, and factory reset to restore benign behavior. The raw data was processed to generate network flows (Zeek logs) which were analyzed and labeled. The dataset contains two types of levels, a high level label and a descriptive label, which were put by experts. The former can take three values, benign, malicious or background. The latter contains detailed information about the specific behavior observed in the network flows. The dataset contains 99 million labeled network flows. The overall compressed size of the dataset is 80GB and the uncompressed size is 170GB.
DOI: 10.5281/zenodo.7973326
title: Biochar amendment to cattle slurry reduces NH3 emissions during storage without risk of higher NH3 emissions after soil application of the solid fraction

description: <strong>Excel files:</strong> - Gas experiment phase 1 and phase 2 + calculation of total emissions - Separation of slurry into solid and liquid fractions - Properties of solid and liquid fractions - Gas experiment soil addition of solid fractions - Soil properties before and after soil application experiment - Calculation of total N losses (gaseous losses + N mineralization) <strong>R-scripts:</strong> - Gas measurements phase 1 and 2 and soil application experiment =&gt; raw data further processed in excel files - Statistics on characteristics and separation efficiency of solid and liquid fraction - Digestaat2022_Significanties: statistics on effect of biochar/application method on emissions and digestate properties
description: The Research Foundation - Flanders (FWO) has (co-)financed the research (BASTA, S000119N).
description: {"references": ["10.1016/j.wasman.2023.0"]}
DOI: 10.5281/zenodo.7973325
title: Biochar amendment to cattle slurry reduces NH3 emissions during storage without risk of higher NH3 emissions after soil application of the solid fraction

description: <strong>Excel files:</strong> - Gas experiment phase 1 and phase 2 + calculation of total emissions - Separation of slurry into solid and liquid fractions - Properties of solid and liquid fractions - Gas experiment soil addition of solid fractions - Soil properties before and after soil application experiment - Calculation of total N losses (gaseous losses + N mineralization) <strong>R-scripts:</strong> - Gas measurements phase 1 and 2 and soil application experiment =&gt; raw data further processed in excel files - Statistics on characteristics and separation efficiency of solid and liquid fraction - Digestaat2022_Significanties: statistics on effect of biochar/application method on emissions and digestate properties
description: The Research Foundation - Flanders (FWO) has (co-)financed the research (BASTA, S000119N).
description: {"references": ["10.1016/j.wasman.2023.0"]}
DOI: 10.6084/m9.figshare.23214140
title: Weddell Sea Bottom Water area timeseries along WOCE sections, A23, A12 and SR4

description: These datasets are the water mass area computed along hydrographic sections showed in Figure 2a in paper "Slowdown of Antarctic Bottom Water export driven by climatic wind and sea-ice changes".
DOI: 10.6084/m9.figshare.23214140.v1
title: Weddell Sea Bottom Water area timeseries along WOCE sections, A23, A12 and SR4

description: These datasets are the water mass area computed along hydrographic sections showed in Figure 2a in paper "Slowdown of Antarctic Bottom Water export driven by climatic wind and sea-ice changes".
DOI: 10.5281/zenodo.7973530
title: RNAseq analysis of Elafibranor and S217879 effects on human PCLS with MAFLD

description: Oxidative stress triggers nonalcoohlic steatohepatitis (NASH) and liver fibrosis. Nuclear-erythroid-2-Related Factor 2 (NRF2) is the master regulation of the anti-oxidant response. In this study, we tested the therapeutic potential of a new NRF2 activator (S217879) in Precision Cut Liver Slices (PCLS) derived from the liver of patients with metabolic associated fatty liver disease (MAFLD), and compared its effects to those of the well-known PPARa/d agonist, Elafibranor.
DOI: 10.5281/zenodo.7973529
title: RNAseq analysis of Elafibranor and S217879 effects on human PCLS with MAFLD

description: Oxidative stress triggers nonalcoohlic steatohepatitis (NASH) and liver fibrosis. Nuclear-erythroid-2-Related Factor 2 (NRF2) is the master regulation of the anti-oxidant response. In this study, we tested the therapeutic potential of a new NRF2 activator (S217879) in Precision Cut Liver Slices (PCLS) derived from the liver of patients with metabolic associated fatty liver disease (MAFLD), and compared its effects to those of the well-known PPARa/d agonist, Elafibranor.
DOI: 10.5281/zenodo.7973569
title: Inverse observation operator parameters/models for master's dissertation: Updating a conceptual rainfall-runoff model based on radar observation and machine learning

description: Both saved models and results of hyperparameter tuning are given. Code related to this dataset can be found here
DOI: 10.5281/zenodo.7973568
title: Inverse observation operator parameters/models for master's dissertation: Updating a conceptual rainfall-runoff model based on radar observation and machine learning

description: Both saved models and results of hyperparameter tuning are given. Code related to this dataset can be found here
DOI: 10.5517/ccdc.csd.cc2f1rjs
title: CCDC 2236015: Experimental Crystal Structure Determination

description: Related Article: lai hanjian|2023|CSD Communication|||
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: 10.5519/qd.4zdso895
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1765 records)
DOI: 10.18170/dvn/gg254w
title: Spatial-temporal distributions of giant magnetofossils

description: Giant magnetofossil grain size
DOI: 10.5519/qd.3kjvnmsd
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (3 records)
DOI: 10.5519/qd.8hmmfjz6
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (8 records)
DOI: 10.57745/wfnjck
title: Sibra_Brunschwig_Field_Data_20230324.tab

description: Field variables (n = 47)
DOI: 10.57745/ckhoyb
title: Sibra_Brunschwig_Data_Dictionnary_20230324.tab

description: Dictionary of farm and field variables
DOI: 10.57745/6izdxp
title: Sibra_Brunschwig_Farm_Data_20230324.tab

description: Farm variables (n = 29)
DOI: 10.5517/ccdc.csd.cc29bnq1
title: CCDC 2125413: Experimental Crystal Structure Determination

description: Related Article: Yan-Hua Fan, Ya-Xin Li, Wen-Jie Zhu, Yan Bai, Dong-Bin Dang|2023|Dyes Pigm.|216|111363|doi:10.1016/j.dyepig.2023.111363
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dlw2z
title: CCDC 2222671: Experimental Crystal Structure Determination

description: Related Article: Guang Che, Weiting Yang, Cong Wang, Meiling Li, Xinyi Li, Yamin Fu, Qinhe Pan|2023|Anal.Chim.Acta|1265|341327|doi:10.1016/j.aca.2023.341327
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2f6vdx
title: CCDC 2240909: Experimental Crystal Structure Determination

description: Related Article: Joanna Bojarska, Martin Breza, Milan Remko, Ye Yuan, Zyta M. Ziora, Tsun-Thai Chai, Izabela D. Madura, Krzysztof Kaczmarek, Mark A.T. Blaskovich, Wojciech M. Wolf|2023|J.Mol.Struct.|1288|135732|doi:10.1016/j.molstruc.2023.135732
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2byy08
title: CCDC 2173720: Experimental Crystal Structure Determination

description: Related Article: Guang Che, Weiting Yang, Cong Wang, Meiling Li, Xinyi Li, Yamin Fu, Qinhe Pan|2023|Anal.Chim.Acta|1265|341327|doi:10.1016/j.aca.2023.341327
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: 10.5281/zenodo.7973593
title: Automatisch erstellter Erdbeben Katalog des Seiger Projektes

description: Dieser Datensatz ist der automatisch vom LIDECT System im Rahmen des Seiger Projektes erstellte Erdbebenkatalog zwischen 2013-2022. Zur Detektion wurde ein Voting basierter Ansatz zwischen Detektionen des EarthquakeTransformer (Mousavi, 2020) und Stacking Detekor genutzt. ML basiertes Denoising aller (Archiv) Daten um Anzahl Phasenpicks zu erhöhen wurde zunächst durchgeführt.<br> Dazu wurde der DeepDenoiser, basierend auf Zhu et al (2019) genutzt, mittels Seisbench (Münchmeyer et al, 2022).<br> Der EarthquakeTransformer wurde durch Transfer learning auf die Zielregion erweitert. Training erfolgte mit Synthetischen Szenario Beben und Picks des MAGS Projektes. Bei Picks von drei Phasen auf unterschiedlichen Stationen, deklariert der EarthquakeTransformer ein Event.<br> Der Stacking Detektor basiert auf linearem stacking für Gridpunkte und nutzt hinterlegte Laufzeitabellen (mehere Geschwindigkeitsmodelle möglich). Einstellungen des Dektektors waren. Δ 1km Grid mit 24km in x,y und 10 km in z, bei 5-45Hz. Stacking erfolgt unter Annahme von P und S Laufzeiten. Wenn die gestackte Energie eines Ereignisses die doppelte Energie des zu dem Zeitpunkt üblichen "noise floors" hat deklariert der Stacking Detektor ein Event. Wenn beide Detektoren ein Event deklariert haben wird ein Erdbeben deklariert und in den Katalog aufgenommen. Picks aus dem EarthquakeTransformer Detektor werden dann zum lokalisieren genutzt mittels Nonlinloc und 1-D Modell (Küperkoch, 2018) des Untergrundes. Ml wird automatisch bestimmt, als auch Mw. Mw wird bestimmt unter Annahme einer Isotroper Quelle. Dazu werden die Daten nach Restitution, BP filtern zwischen 5 und 45 Hz mit synthetischen Daten verglichen. Dieses fitting von absoluten Amplituden Werten und Zeit erfolgt an allen beteiligten Stationen gleichzeitig.<br> Tiefe und Lokalität werden festgehalten auf Basis der Nonlinloc Lokalität.<br> Mousa
DOI: 10.5281/zenodo.7973592
title: Automatisch erstellter Erdbeben Katalog des Seiger Projektes

description: Dieser Datensatz ist der automatisch vom LIDECT System im Rahmen des Seiger Projektes erstellte Erdbebenkatalog zwischen 2013-2022. Zur Detektion wurde ein Voting basierter Ansatz zwischen Detektionen des EarthquakeTransformer (Mousavi, 2020) und Stacking Detekor genutzt. ML basiertes Denoising aller (Archiv) Daten um Anzahl Phasenpicks zu erhöhen wurde zunächst durchgeführt.<br> Dazu wurde der DeepDenoiser, basierend auf Zhu et al (2019) genutzt, mittels Seisbench (Münchmeyer et al, 2022).<br> Der EarthquakeTransformer wurde durch Transfer learning auf die Zielregion erweitert. Training erfolgte mit Synthetischen Szenario Beben und Picks des MAGS Projektes. Bei Picks von drei Phasen auf unterschiedlichen Stationen, deklariert der EarthquakeTransformer ein Event.<br> Der Stacking Detektor basiert auf linearem stacking für Gridpunkte und nutzt hinterlegte Laufzeitabellen (mehere Geschwindigkeitsmodelle möglich). Einstellungen des Dektektors waren. Δ 1km Grid mit 24km in x,y und 10 km in z, bei 5-45Hz. Stacking erfolgt unter Annahme von P und S Laufzeiten. Wenn die gestackte Energie eines Ereignisses die doppelte Energie des zu dem Zeitpunkt üblichen "noise floors" hat deklariert der Stacking Detektor ein Event. Wenn beide Detektoren ein Event deklariert haben wird ein Erdbeben deklariert und in den Katalog aufgenommen. Picks aus dem EarthquakeTransformer Detektor werden dann zum lokalisieren genutzt mittels Nonlinloc und 1-D Modell (Küperkoch, 2018) des Untergrundes. Ml wird automatisch bestimmt, als auch Mw. Mw wird bestimmt unter Annahme einer Isotroper Quelle. Dazu werden die Daten nach Restitution, BP filtern zwischen 5 und 45 Hz mit synthetischen Daten verglichen. Dieses fitting von absoluten Amplituden Werten und Zeit erfolgt an allen beteiligten Stationen gleichzeitig.<br> Tiefe und Lokalität werden festgehalten auf Basis der Nonlinloc Lokalität.<br> Mousa
DOI: 10.6084/m9.figshare.23214491
title: Downscaled_GWSA_dataset

description: This file contains the model program and input data files, and downscaled groundwater storage changes(GWSC) dataset.
DOI: 10.6084/m9.figshare.23214491.v1
title: Downscaled_GWSA_dataset

description: This file contains the model program and input data files, and downscaled groundwater storage changes(GWSC) dataset.
DOI: 10.6084/m9.figshare.23214794
title: Downscaled_GWSC_dataset

description: This file contains the model program and input data files, and downscaled groundwater storage changes(GWSC) dataset.
DOI: 10.6084/m9.figshare.23214794.v1
title: Downscaled_GWSC_dataset

description: This file contains the model program and input data files, and downscaled groundwater storage changes(GWSC) dataset.
DOI: 10.4121/862a0b6e-c1af-48f0-b4b1-af093b28d1e8.v1
title: Data underlying the publication: Effects of spatial resolution on the prediction performance of species distribution models: Case study of Skipjack tuna in the Western and Central Pacific Ocean

description: Fishing effort data derived from Automatic Identification System (AIS) in 2012 -2020, Global fishing watch Data were obtained from https://globalfishingwatch.org/TW logbook data are available from the corresponding author, [Y, Chang], upon reasonable request. *yichang@mail.nsysu.edu.tw
DOI: 10.6084/m9.figshare.23214956
title: Environmental_data_seagrape_ponds_MANTA.xlsx

description: The data set contains enviornmental parameter quantififed at a sea grape farm in Van Phong Bay, Viet Nam. More information, including details on the location are included in the publication.
DOI: 10.6084/m9.figshare.23214956.v1
title: Environmental_data_seagrape_ponds_MANTA.xlsx

description: The data set contains enviornmental parameter quantififed at a sea grape farm in Van Phong Bay, Viet Nam. More information, including details on the location are included in the publication.
DOI: 10.15151/esrf-es-1161652773
title: Cryo-EM sample preparation workshop participants samples

description: The cryo-EM sample preparation workshop is scheduled for the 23-25 May 2023. this proposal is to include samples that will be brought by the workshop participants. The compiled sample sheets will then be submitted to safety later for their review.
DOI: 10.6084/m9.figshare.23214950.v1
title: Environmental_data_seagrape_ponds_LOGGER.xlsx

description: The data set contains enviornmental parameter quantififed at a sea grape farm in Van Phong Bay, Viet Nam. More information, including details on the location are included in the publication.
DOI: 10.6084/m9.figshare.23214950
title: Environmental_data_seagrape_ponds_LOGGER.xlsx

description: The data set contains enviornmental parameter quantififed at a sea grape farm in Van Phong Bay, Viet Nam. More information, including details on the location are included in the publication.
DOI: 10.5281/zenodo.7973745
title: Assessment of kisspeptin and trappin level in Iraqi women with early pregnancy loss: an observation study

description: Assessment of kisspeptin and trappin level in Iraqi women with early pregnancy loss: an observation study
DOI: 10.5281/zenodo.7973744
title: Assessment of kisspeptin and trappin level in Iraqi women with early pregnancy loss: an observation study

description: Assessment of kisspeptin and trappin level in Iraqi women with early pregnancy loss: an observation study
DOI: 10.5281/zenodo.7973774
title: Preprocessing output for master's dissertation: Updating a conceptual rainfall-runoff model based on radar observation and machine learning

description: Outputs of the local preprocessing of the OpenEO data (see here) and pywaterinfo data (see here). Code related to this dataset can be found here
DOI: 10.5281/zenodo.7973773
title: Preprocessing output for master's dissertation: Updating a conceptual rainfall-runoff model based on radar observation and machine learning

description: Outputs of the local preprocessing of the OpenEO data (see here) and pywaterinfo data (see here). Code related to this dataset can be found here
DOI: 10.25345/c56t0h62h
title: MassIVE MSV000092036 - Lipidomics analysis of salivary glands of Ixodes ricinus
title: Lipidomics analysis of salivary glands of Ixodes ricinus
DOI: 10.18112/openneuro.ds004548.v1.0.1
title: A testbed for development and comparison of multi-modal brain MRI harmonisation approaches
DOI: 10.5281/zenodo.7971336
title: RNAseq of E. coli

description: RNAseq subset.
DOI: 10.5281/zenodo.7971337
title: RNAseq of E. coli

description: RNAseq subset.
DOI: 10.5281/zenodo.7973603
title: RNAseq of E. coli

description: RNAseq subset.
DOI: 10.5281/zenodo.7966849
title: IL-17 signalling is critical for controlling subcutaneous adipose tissue dynamics and parasite burden during chronic Trypanosoma brucei infection

description: In the skin, <em>Trypanosoma brucei </em>colonises the subcutaneous white adipose tissue (WAT) and harbours a pool of parasites competent for forward transmission. The interaction between parasites, adipose tissue, and the local immune system is likely to drive adipose tissue wasting and weight loss observed in cattle and humans infected with <em>T. brucei</em>. However, mechanistically, this process is not fully understood. Here, using several complementary approaches including mass cytometry by time of flight, bulk and single cell transcriptomics, we found that <em>T. brucei</em> infection drives a local expansion of several IL-17A-producing cells in the murine WAT, including T<sub>H</sub>17 and Vg6<sup>+</sup> T cells. We also found that global IL-17 deficiency, or mice lacking IL-17 receptor expression specifically on adipocytes, were protected from infection-induced WAT wasting and weight loss. Unexpectedly, we found that abrogation of IL-17 signalling on adipocytes results in higher burden of extravascular parasites in the WAT. Taken together, our study highlights the central role of IL-17 signalling on adipocytes in controlling WAT responses to infection, suggesting that adipocytes are a critical coordinator of the tissue immune response to <em>T. brucei</em> infection.