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Abstract For more than three decades, satellite altimetry has provided valuable measurement data for the monitoring and analysis of ocean and inland water surfaces. Since 1992, there have always been at least two simultaneous missions providing continuous measurement data, starting with TOPEX/Poseidon and ERS‐1 in the early 1990s and continuing with about 10 satellites active today, including ICESat‐2, Sentinel‐6A and SWOT. Most mission data are freely available, but in different formats, processing levels and with respect to different references (e.g. ellipsoid or time), making common multi‐mission applications difficult. In addition, the derivation of ready‐to‐use and high‐quality scientific products requires expertise that not every user is willing to acquire. Over the years, DGFI‐TUM has developed and maintained an Open Altimeter Database (OpenADB) that allows consistent data management and combination. It consists of the internal Multi‐Version Altimetry (MVA) data repository and the OpenADB web portal. OpenADB provides user‐friendly access to derived along‐track products, such as sea surface heights and ocean tides. It also provides general information about the satellite altimetry missions, their observing configurations and about the data provided in the database. All products are freely available on the OpenADB web portal (https://openadb.dgfi.tum.de) after registration.

Abstract The global reach-scale “ICESat-2 River Surface Slope” (IRIS) dataset comprises average and extreme water surface slopes (WSS) derived from ICESat-2 observations between October 2018 and August 2022 as a supplement to 121,583 reaches from the “SWOT Mission River Database” (SWORD). To gain full advantage of ICESat-2’s unique measurement geometry with six parallel lidar beams, the WSS is determined across pairs of beams or along individual beams, depending on the intersection angle of spacecraft orbit and river centerline. Combining both approaches maximizes spatial and temporal coverage. IRIS can be used to research river dynamics, estimate river discharge, and correct water level time series from satellite altimetry for shifting ground tracks. Additionally, by referencing SWORD as a common database, IRIS may be used in combination with observations from the recently launched SWOT mission.

A 23-year-old male patient presented with very mild visual disturbances, but a distinct prominence of the optic discs, more pronounced in the right than in the left eye. The ophthalmic symptoms initially seemed trivial, but a large-scale interdisciplinary workup later identified them as the presenting symptoms of sarcoidosis affecting lung and eyes. A standard steroid monotherapy successfully caused regression of the ophthalmic findings.

Remote sensing data are essential for monitoring the Earth’s surface waters, especially since the amount of publicly available in-situ data is declining. Satellite altimetry provides valuable information on the water levels and variations of lakes, reservoirs and rivers. In combination with satellite imagery, the derived time series allow the monitoring of lake storage changes and river discharge. However, satellite altimetry is limited in terms of its spatial resolution due to its measurement geometry, only providing information in the nadir direction beneath the satellite’s orbit. In a case study in the Mississippi River Basin (MRB), this study investigates the potential and limitations of past and current satellite missions for the monitoring of basin-wide storage changes. For that purpose, an automated target detection is developed and the extracted lake surfaces are merged with the satellites’ tracks. This reveals that the current altimeter configuration misses about 80% of all lakes larger than 0.1 km2 in the MRB and 20% of lakes larger than 10 km2, corresponding to 30% and 7% of the total water area, respectively. Past altimetry configurations perform even more poorly. From the larger water bodies represented by a global hydrology model, at least 91% of targets and 98% of storage changes are captured by the current altimeter configuration. This will improve significantly with the launch of the planned Surface Water and Ocean Topography (SWOT) mission.

Despite increasing interest in monitoring the global water cycle, the availability of in situ gauging and discharge time series is decreasing. However, this lack of ground data can partly be compensated for by using remote sensing techniques to observe river stages and discharge. In this paper, a new approach for estimating discharge by combining water levels from multi-mission satellite altimetry and surface area extents from optical imagery with physical flow equations at a single cross-section is presented and tested at the Lower Mississippi River. The datasets are combined by fitting a hypsometric curve, which is then used to derive the water level for each acquisition epoch of the long-term multi-spectral remote sensing missions. In this way, the chance of detecting water level extremes is increased and a bathymetry can be estimated from water surface extent observations. Below the minimum hypsometric water level, the river bed elevation is estimated using an empirical width-to-depth relationship in order to determine the final cross-sectional geometry. The required flow gradient is derived from the differences between virtual station elevations, which are computed in a least square adjustment from the height differences of all multi-mission satellite altimetry data that are close in time. Using the virtual station elevations, satellite altimetry data from multiple virtual stations and missions are combined to one long-term water level time series. All required parameters are estimated purely based on remote sensing data, without using any ground data or calibration. The validation at three gauging stations of the Lower Mississippi River shows large deviations primarily caused by the below average width of the predefined cross-sections. At 13 additional cross-sections situated in wide, uniform, and straight river sections nearby the gauges the Normalized Root Mean Square Error (NRMSE) varies between 10.95% and 28.43%. The Nash-Sutcliffe Efficiency (NSE) for these targets is in a range from 0.658 to 0.946.

In this study, a new approach for the automated extraction of high-resolution time-variable water surfaces is presented. For that purpose, optical images from Landsat and Sentinel-2 are used between January 1984 and June 2018. The first part of this new approach is the extraction of land-water masks by combining five water indexes and using an automated threshold computation. In the second part of this approach, all data gaps caused by voids, clouds, cloud shadows, or snow are filled by using a long-term water probability mask. This mask is finally used in an iterative approach for filling remaining data gaps in all monthly masks which leads to a gap-less surface area time series for lakes and reservoirs. The results of this new approach are validated by comparing the surface area changes with water level time series from gauging stations. For inland waters in remote areas without in situ data water level time series from satellite altimetry are used. Overall, 32 globally distributed lakes and reservoirs of different extents up to 2482.27 km 2 are investigated. The average correlation coefficients between surface area time series and water levels from in situ and satellite altimetry have increased from 0.611 to 0.862 after filling the data gaps which is an improvement of about 41%. This new approach clearly demonstrates the quality improvement for the estimated land-water masks but also the strong impact of a reliable data gap-filling approach. All presented surface area time series are freely available on the Database of Hydrological Time Series of Inland (DAHITI).

Este artigo descreve a criação de um protótipo de um robô móvel, com finalidade educacional utilizando a plataforma Arduino, tendo como principal finalidade simplificar o uso desta plataforma, eliminando a necessidade de conhecimentos complexos em determinados níveis de ensino como bem como de oferecer uma alternativa a os kits disponíveis no mercado com custos relativamente acessíveis.

Cardiac inwardly rectifying Kir current (IK1) mediates terminal repolarisation and is critical for the stabilization of the diastolic membrane potential. Its predominant molecular basis in mammalian ventricle is heterotetrameric assembly of Kir2.1 and Kir2.2 channel subunits. It has been shown that PKC inhibition of IK1 promotes focal ventricular ectopy. However, the underlying molecular mechanism has not been fully elucidated to date.In the Xenopus oocyte expression system, we observed a pronounced PKC-induced inhibition of Kir2.2 but not Kir2.1 currents. The PKC regulation of Kir2.2 could be reproduced by an activator of conventional PKC isoforms and antagonized by pharmacological inhibition of PKCβ. In isolated ventricular cardiomyocytes (rat, mouse), pharmacological activation of conventional PKC isoforms induced a pronounced inhibition of IK1. The PKC effect in rat ventricular cardiomyocytes was markedly attenuated following co-application of a small molecule inhibitor of PKCβ. Underlining the critical role of PKCβ, the PKC-induced inhibition of IK1 was absent in homozygous PKCβ knockout-mice. After heterologous expression of Kir2.1-Kir2.2 concatemers in Xenopus oocytes, heteromeric Kir2.1/Kir2.2 currents were also inhibited following activation of PKC.We conclude that inhibition of cardiac IK1 by PKC critically depends on the PKCβ isoform and Kir2.2 subunits. This regulation represents a potential novel target for the antiarrhythmic therapy of focal ventricular arrhythmias.