cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10685538
title: Supporting materials for "Direction-aware functional class scoring enrichment analysis of Infinium DNA methylation data"

description: Here are the supporting information for the manuscript entitled "Direction-aware functional class scoring enrichment analysis of Infinium DNA methylation data". The article describes a method for accurate pathway enrichment analysis of Infinium Methylation array data.

This archive contains the software repository for the project at time of public release, a docker image to facilitate reproduction, a copy of the preprint and an R Markdown generated HTML report that demonstrates a simple application of the method as mentioned in the preprint. 

The PDF file "Direction-aware FCS V2.3 preprint.pdf" is the preprint. The "gmea.tar.gz" file is the docker image. The "gmea-main.zip" file is the git software repository. The "example_workflow.html" file is the HTML report.
DOI: 10.34740/kaggle/dsv/7667043
title: Billboard charts
DOI: 10.6084/m9.figshare.25246696
title: data.zip

description: This research investigates how the intervention of state-sponsored media influences public opinion and gender ideology. The research compares changes in the themes, sentiments, and psychological characteristics of netizens' comments before and after state-sponsored media intervention in an Internet gender event. The research also explains the relationship between the state intervention and the dynamics of public opinion and gender ideology, thereby establishing a corresponding theoretical framework.
DOI: 10.6084/m9.figshare.25246696.v1
title: data.zip

description: This research investigates how the intervention of state-sponsored media influences public opinion and gender ideology. The research compares changes in the themes, sentiments, and psychological characteristics of netizens' comments before and after state-sponsored media intervention in an Internet gender event. The research also explains the relationship between the state intervention and the dynamics of public opinion and gender ideology, thereby establishing a corresponding theoretical framework.
DOI: 10.1594/pangaea.843151
title: Downscaled land surface temperatures obtained by a particle smoothing approach, with links to NetCDF files

description: This dataset contains continuous time series of land surface temperature (LST) at spatial resolution of 300m around the 12 experimental sites of the PAGE21 project (grant agreement number 282700, funded by the EC seventh Framework Program theme FP7-ENV-2011). This dataset was produced from hourly LST time series at 25km scale, retrieved from SSM/I data (André et al., 2015, doi:10.1016/j.rse.2015.01.028) and downscaled to 300m using a dynamic model and a particle smoothing approach. This methodology is based on two main assumptions. First, LST spatial variability is mostly explained by land cover and soil hydric state. Second, LST is unique for a land cover class within the low resolution pixel. Given these hypotheses, this variable can be estimated using a land cover map and a physically based land surface model constrained with observations using a data assimilation process. This methodology described in Mechri et al. (2014, doi:10.1002/2013JD020354) was applied to the ORCHIDEE land surface model (Krinner et al., 2005, doi:10.1029/2003GB002199) to estimate prior values of each land cover class provided by the ESA CCI-Land Cover product (Bontemps et al., 2013) at 300m resolution . The assimilation process (particle smoother) consists in simulating ensemble of LST time series for each land cover class and for a large number of parameter sets. For each parameter set, the resulting temperatures are aggregated considering the grid fraction of each land cover and compared to the coarse observations. Miniminizing the distance between the aggregated model solutions and the observations allow us to select the simulated LST and the corresponding parameter sets which fit the observations most closely. The retained parameter sets are then duplicated and randomly perturbed before simulating the next time window. At the end, the most likely LST of each land cover class are estimated and used to reconstruct LST maps at 300m resolution using ESA CCI-Land Cover. The resulting temperature maps on which ice pixels were masked, are provided at daily time step during the nine-year analysis period (2000-2009).
description: Supplement to: André, Cyrille; Ottlé, Catherine; Mechri, Rihab; Pannekoucke, Olivier; Maignan, Fabienne (2015): SSM/I Land Surface Temperature downscaling over Arctic sites.
DOI: 10.1594/pangaea.932530
title: Basic measurements of radiation at station Reunion Island, University (2019-06)
DOI: 10.1594/pangaea.931193
title: Basic measurements of radiation at station Reunion Island, University (2021-04)
DOI: 10.1594/pangaea.930944
title: Basic measurements of radiation at station Reunion Island, University (2019-08)
DOI: 10.1594/pangaea.930945
title: Basic measurements of radiation at station Reunion Island, University (2019-09)
DOI: 10.1594/pangaea.930946
title: Basic measurements of radiation at station Reunion Island, University (2019-10)
DOI: 10.1594/pangaea.930948
title: Basic measurements of radiation at station Reunion Island, University (2019-11)
DOI: 10.1594/pangaea.930949
title: Basic measurements of radiation at station Reunion Island, University (2019-12)
DOI: 10.1594/pangaea.930975
title: Basic measurements of radiation at station Reunion Island, University (2020-01)
DOI: 10.1594/pangaea.930984
title: Basic measurements of radiation at station Reunion Island, University (2020-02)
DOI: 10.1594/pangaea.930985
title: Basic measurements of radiation at station Reunion Island, University (2020-03)
DOI: 10.1594/pangaea.930986
title: Basic measurements of radiation at station Reunion Island, University (2020-04)
DOI: 10.1594/pangaea.930987
title: Basic measurements of radiation at station Reunion Island, University (2020-06)
DOI: 10.1594/pangaea.930988
title: Basic measurements of radiation at station Reunion Island, University (2020-07)
DOI: 10.1594/pangaea.930989
title: Basic measurements of radiation at station Reunion Island, University (2020-08)
DOI: 10.1594/pangaea.930990
title: Basic measurements of radiation at station Reunion Island, University (2020-09)
DOI: 10.1594/pangaea.930991
title: Basic measurements of radiation at station Reunion Island, University (2020-10)
DOI: 10.1594/pangaea.930992
title: Basic measurements of radiation at station Reunion Island, University (2020-11)
DOI: 10.1594/pangaea.930993
title: Basic measurements of radiation at station Reunion Island, University (2020-12)
DOI: 10.1594/pangaea.930995
title: Basic measurements of radiation at station Reunion Island, University (2021-01)
DOI: 10.1594/pangaea.930996
title: Basic measurements of radiation at station Reunion Island, University (2021-02)
DOI: 10.1594/pangaea.930997
title: Basic measurements of radiation at station Reunion Island, University (2021-03)
DOI: 10.1594/pangaea.929500
title: Prioritised pharmaceuticals in German estuaries and coastal waters in 2015/2016

description: In this study a target analysis approach with method detection limits down to 0.01 ng L−1 was developed in order to determine ultra-trace pharmaceuticals in seawater of the German coast and their estuaries. The selection of target analytes based on a prioritisation commissioned by the German Environmental Agency considering occurrence in German surface waters, production volumes and ecotoxicological data. Using ultra-high pressure liquid chromatography coupled to a triple quadrupole mass spectrometer equipped with an electrospray ionisation source 21 prioritised pharmaceuticals out of seven therapeutical classes (antibiotics, iodinated X-ray contrast media (ICM), analgesics, lipid reducers, antiepileptics, anticonvulsants, beta-blockers) have been detected in the low to medium ng L−1-range. The most frequently measured substance groups in the German Baltic Sea and German Bight are the ICM, represented by the non-ionic ICM iomeprol (German Bightmax: 207 ng L−1; Baltic Seamax: 34.5 ng L−1) and the ionic ICM amidotrizoic acid (German Bight: 86.9 ng L−1), respectively. The same pattern of substance distribution could be detected in the German Bight, the German Baltic Sea and their inflows with lower concentrations in the offshore region that are partly a result of dilution with marine water. Pharmaceuticals entering the estuaries and coastal regions are an environmental issue since data on the ecotoxicological effects on aquatic marine organisms is limited. Especially the antibiotics clarithromycin and sulfamethoxazole could be ecotoxicologically/environmentally critical.
description: Date/Time = local timeTemperature, water; Salinity and pH method:For campaigns SB1603 and SB1508: oxygen, conductivity, temperature, pH; Multimeter 3430 WTW. For campaign LP20150529: Measurement by on-line-in-situ FerryBox-System.
DOI: 10.1594/pangaea.932531
title: Basic measurements of radiation at station Reunion Island, University (2019-07)
DOI: 10.1594/pangaea.932532
title: Basic measurements of radiation at station Reunion Island, University (2020-05)
DOI: 10.1594/pangaea.932695
title: Basic measurements of radiation at station Reunion Island, University (2021-05)
DOI: 10.1594/pangaea.933150
title: Height, diameter, biomass, leaf area, and relative height volume growth of European beech, Norway spruce, and Douglas fir grown in monospecific and mixed pots under different light availability levels

description: Light is an exceptionally important but often limited resource. Light availability determines seedling survival, establishment, and growth. Regardless of species identity, trees growing under high light availability produce more biomass and are generally larger than trees receiving less light. How stressed trees become under the conditions of limited light availability depends on species-specific factors like shade tolerance and plasticity as well as the competitive situation. Additionally, the taller individuals have the advantage to obtain more light since competition for the resource is asymmetric. In competitive environments, the niche complementarity of the coexisting species can reduce the competitive pressure and facilitate higher biomass production (i.e., positive mixing effect). We established a controlled pot experiment to study the effect of light availability and competition type on growth and its allocation, biomass production and allocation, and leaf morphology of European beech (Fagus sylvatica L.), Norway spruce (Picea abies L. Karst), and Douglas fir (Pseudotsuga menziesii Mirb. Franco) seedlings. The study site was located at the Experimental Botanical Garden of the University of Göttingen (51.55684392372871, 9.953489533796636). We planted four seedlings per pot, each pot being either monospecific or mixed (two seedlings per species) and exposed to one of three different light availability levels (10%, 20%, and 50%). We planted in a total of 576 pots – 6 species combinations (monocultures + mixtures) x 3 light treatment levels x 32 replicates. For planting, we used 1-year-old European beech and 2-year-old Norway spruce and Douglas fir seedlings that were not undercut or transplanted. The experiment lasted from April 2018 – November 2019. All seedlings received the same water treatment through an automatic dripping irrigation system. Nutrients were provided using a controlled release fertilizer (Osmocote Exact Hi.End with 12-14 month longevity (ICL SF)).
description: Relative Height Volume Growth (R) measures the share of the volume growth over one growing season that can be attributed to height growth alone. It is defined as $$ R = \frac{\Delta V_H}{\Delta V} = \frac{\pi \cdot (D_1 / 2)^2 \cdot H_2 - \pi \cdot (D_1 / 2)^2 \cdot H_1}{\pi \cdot (D_2 / 2)^2 \cdot H_2 - \pi \cdot (D_1 / 2)^2 \cdot H_1} = \frac{D_1^2 \cdot (H_2 - H_1)}{D_2^2 \cdot H_2 - D_1^2 \cdot H_1}, $$, where \Delta V_H is the volume growth due to height growth, and \Delta V is the total volume growth over one growing season. Furthermore, H_1 and H_2 are the height at the beginning and the end of the growing season, and D_1 and D_2 are the diameter at the beginning and the end of the growing season. Without measurement errors, the variable 'Relative Height Volume Growth' should take values in the interval [0,1]. All values outside of this interval have been removed.
DOI: 10.1594/pangaea.934990
title: Basic measurements of radiation at station Reunion Island, University (2021-07)

description: Early morning and late afternoon missing radiation data due to the building mask of the temporary station installation. Those masks appear between 30th July and 17th September and should be corrected by the station installation on the new elevated platform.
DOI: 10.1594/pangaea.940759
title: Post-processed, gap-filled and partitioned carbon and energy fluxes from eddy-covariance measurements above the forest ecosystem Hohes Holz in 2015

description: Carbon dioxide, water vapour and energy fluxes from eddy-covariance measurements after post-processing and gap-filling with the REddyProc package (Wutzler, T., et al., 2018) combined with selected environmental variables measured (or derived) at the same site at the EC tower with Campbell Scientific data loggers. Flags describe quality of data after e.g. checks for stationarity and intergral turbulence characteristics (Foken, T. and Wichura, B., 1996), or the ability of gap-filling (Wutzler, T., et al., 2018) and represent either good (0), suspicious (1) or bad (2) data. Net ecosystem exchange of CO2 (NEE) is partitioned into gross primary productivity (GPP) and ecosystem respiration (Reco) by different procedures (Lasslop, et al., 2010, Reichstein et al., 2005). '-9999' is indicating missing values.
DOI: 10.1594/pangaea.933811
title: Basic measurements of radiation at station Reunion Island, University (2021-06)
DOI: 10.1594/pangaea.939031
title: Basic measurements of radiation at station Reunion Island, University (2021-11)
DOI: 10.1594/pangaea.940271
title: Processed seawater temperature, conductivity and salinity obtained at different depths by CTD buoy 2019O1 as part of the MOSAiC Distributed Network

description: CTD buoy 2019O1 was deployed in the MOSAiC Distributed Network in the Northern Laptev Sea in early October 2019 as part of a set of eight identical ice-tethered buoy systems, each consisting of 5 Seabird SBE37IMP Microcat CTDs mounted along an inductive modem tether at depths of 10, 20, 50, 75 and 100m. The CTDs were recording oceanographic data internally at 2-minute intervals. The surface unit of the buoy prompted the instruments for an additional measurement every 10 minutes, which was then transmitted to a base station via iridium along with GPS position and time, as well as surface temperature. After 305 days of drift through the Central Arctic Ocean, 2019O1 was recovered in August 2020, and the internally recorded data from the CTDs were secured. The 10-minute buoy data and 2-minute CTD data were co-processed and merged into a combined product. A buoy flag indicates whether a measurement was taken by the buoy (1) or was recorded by the CTD itself (0). The data were quality controlled by means of outlier detection using global limits, moving average filters and manual inspection. The dataset was carefully checked for inconsistencies, especially in the salinity. Where appropriate, parameters were modified to enhance the quality. A (slightly modified) quality flagging scheme was applied according to the Ocean Data Standards Volume 3 (UNESCO 2013), where 1 = Good, 2 = Good (Modified), 3 = Questionable, 4 = Bad, 9 = no data. Finally, the data were validated against independent measurements. Details are available in the data paper indicted below.
description: • GearID 1: SBE37IMP, SN 21089• GearID 2: SBE37IMP, SN 21090• GearID 3: SBE37IMP, SN 21091• GearID 4: SBE37IMP, SN 21092• GearID 5: SBE37IMP, SN 21082Acknowledgments:The data were produced as part of the international Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) with the tag MOSAiC20192020 (grant numbers AWI_PS122_00 and AFMOSAiC-1_00). The instruments were funded through the MIDO (Multidisciplinary Ice-based Drifting Observatory) infrastructure program, and built by Pacific Gyre, USA. We thank the crews of the research vessels Akademik Fedorov, Akademik Tryoshnikov and RV Polarstern, and in particular the chief scientists, Thomas Krumpen and Markus Rex. We thank the helicopter company Naryan-Marsky for their great logistical support that made this effort possible. We express our gratitude to all participants of these expeditions, and particularly to the MOSAiC School for their field assistance during the set-up. We appreciate the efforts of Kirstin Schulz, Julia Regnery, Ingo Schuffenhauer, Morven Muilwijk, Sandra Tippenhauer and the entire Leg 4 Team for the recovery of the instruments.
DOI: 10.1594/pangaea.940282
title: Processed seawater temperature, conductivity and salinity obtained at different depths by CTD buoy 2019O3 as part of the MOSAiC Distributed Network

description: CTD buoy 2019O3 was deployed in the MOSAiC Distributed Network in the Northern Laptev Sea in early October 2019 as part of a set of eight identical ice-tethered buoy systems, each consisting of 5 Seabird SBE37IMP Microcat CTDs mounted along an inductive modem tether at depths of 10, 20, 50, 75 and 100m. The CTDs were recording oceanographic data internally at 2-minute intervals. The surface unit of the buoy prompted the instruments for an additional measurement every 10 minutes, which was then transmitted to a base station via iridium along with GPS position and time, as well as surface temperature. After 301 days of drift through the Central Arctic Ocean, 2019O3 was recovered in August 2020, and the internally recorded data from the CTDs were secured. The 10-minute buoy data and 2-minute CTD data were co-processed and merged into a combined product. A buoy flag indicates whether a measurement was taken by the buoy (1) or was recorded by the CTD itself (0). The data were quality controlled by means of outlier detection using global limits, moving average filters and manual inspection. The dataset was carefully checked for inconsistencies, especially in the salinity. Where appropriate, parameters were modified to enhance the quality. A (slightly modified) quality flagging scheme was applied according to the Ocean Data Standards Volume 3 (UNESCO 2013), where 1 = Good, 2 = Good (Modified), 3 = Questionable, 4 = Bad, 9 = no data. Finally, the data were validated against independent measurements. Details are available in the data paper indicted below.
description: • GearID 1: SBE37IMP, SN 21100• GearID 2: SBE37IMP, SN 21103• GearID 3: SBE37IMP, SN 21113• GearID 4: SBE37IMP, SN 21114• GearID 5: SBE37IMP, SN 21084Acknowledgments:The data were produced as part of the international Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) with the tag MOSAiC20192020 (grant numbers AWI_PS122_00 and AFMOSAiC-1_00). The instruments were funded through the MIDO (Multidisciplinary Ice-based Drifting Observatory) infrastructure program, and built by Pacific Gyre, USA. We thank the crews of the research vessels Akademik Fedorov, Akademik Tryoshnikov and RV Polarstern, and in particular the chief scientists, Thomas Krumpen and Markus Rex. We thank the helicopter company Naryan-Marsky for their great logistical support that made this effort possible. We express our gratitude to all participants of these expeditions, and particularly to the MOSAiC School for their field assistance during the set-up. We appreciate the efforts of Kirstin Schulz, Julia Regnery, Ingo Schuffenhauer, Morven Muilwijk, Sandra Tippenhauer and the entire Leg 4 Team for the recovery of the instruments.
DOI: 10.1594/pangaea.940291
title: Processed seawater temperature, conductivity and salinity obtained at different depths by CTD buoy 2019O4 as part of the MOSAiC Distributed Network

description: CTD buoy 2019O4 was deployed in the MOSAiC Distributed Network in the Northern Laptev Sea in early October 2019 as part of a set of eight identical ice-tethered buoy systems, each consisting of 5 Seabird SBE37IMP Microcat CTDs mounted along an inductive modem tether at depths of 10, 20, 50, 75 and 100m. The CTDs were recording oceanographic data internally at 2-minute intervals. The surface unit of the buoy prompted the instruments for an additional measurement every 10 minutes, which was then transmitted to a base station via iridium along with GPS position and time, as well as surface temperature. After 311 days of drift through the Central Arctic Ocean, 2019O4 was recovered in August 2020, and the internally recorded data from the CTDs were secured. The 10-minute buoy data and 2-minute CTD data were co-processed and merged into a combined product. A buoy flag indicates whether a measurement was taken by the buoy (1) or was recorded by the CTD itself (0). The data were quality controlled by means of outlier detection using global limits, moving average filters and manual inspection. The dataset was carefully checked for inconsistencies, especially in the salinity. Where appropriate, parameters were modified to enhance the quality. A (slightly modified) quality flagging scheme was applied according to the Ocean Data Standards Volume 3 (UNESCO 2013), where 1 = Good, 2 = Good (Modified), 3 = Questionable, 4 = Bad, 9 = no data. Finally, the data were validated against independent measurements. Details are available in the data paper indicted below.
description: • GearID 1: SBE37IMP, SN 21093• GearID 2: SBE37IMP, SN 21094• GearID 3: SBE37IMP, SN 21095• GearID 4: SBE37IMP, SN 21099• GearID 5: SBE37IMP, SN 21083Acknowledgments:The data were produced as part of the international Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) with the tag MOSAiC20192020 (grant numbers AWI_PS122_00 and AFMOSAiC-1_00). The instruments were funded through the MIDO (Multidisciplinary Ice-based Drifting Observatory) infrastructure program, and built by Pacific Gyre, USA. We thank the crews of the research vessels Akademik Fedorov, Akademik Tryoshnikov and RV Polarstern, and in particular the chief scientists, Thomas Krumpen, Markus Rex and Matthew Shupe. We thank the helicopter company Naryan-Marsky for their great logistical support that made this effort possible. We express our gratitude to all participants of these expeditions, and particularly to the MOSAiC School for their field assistance during the set-up. We appreciate the efforts of Kirstin Schulz, Julia Regnery, Ingo Schuffenhauer, Morven Muilwijk, Sandra Tippenhauer and the entire Leg 4 Team for the recovery of the instruments.