Regional comparison of absolute gravimeters, EURAMET.M.G-K2 key comparison

In the framework of the regional EURAMET.M.G-K2 comparison of absolute gravimeters, 17 gravimeters were compared in November 2015. Four gravimeters were from different NMIs and DIs, they were used to link the regional comparison to the CCM.G.K2 by means of linking converter. Combined least-squares adjustments with weighted constraint was used to determine KCRV. Several pilot solutions are presented and compared with the official solution to demonstrate influences of different approaches (e.g. definition of weights and the constraint) on results of the adjustment. In case of the official solution, all the gravimeters are in equivalence with declared uncertainties. == Main text To reach the main text of this paper, click on Final Report [http://www.bipm.org/utils/common/pdf/final_reports/M/G-K2/EURAMET.M.G-K2.pdf] . Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/ [http://kcdb.bipm.org/] . The final report has been peer-reviewed and approved for publication by the CCM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA)

Computer Vision Algorithms of DigitSeis for Building a Vectorised Dataset of Historical Seismograms from the Archive of Royal Observatory of Belgium

Archived seismograms recorded in the 20th century present a valuable source of information for monitoring earthquake activity. However, old data, which are only available as scanned paper-based images should be digitised and converted from raster to vector format prior to reuse for geophysical modelling. Seismograms have special characteristics and specific features recorded by a seismometer and encrypted in the images: signal trace lines, minute time gaps, timing and wave amplitudes. This information should be recognised and interpreted automatically when processing archives of seismograms containing large collections of data. The objective was to automatically digitise historical seismograms obtained from the archives of the Royal Observatory of Belgium (ROB). The images were originally recorded by the Galitzine seismometer in 1954 in Uccle seismic station, Belgium. A dataset included 145 TIFF images which required automatic approach of data processing. Software for digitising seismograms are limited and many have disadvantages. We applied the DigitSeis for machine-based vectorisation and reported here a full workflow of data processing. This included pattern recognition, classification, digitising, corrections and converting TIFFs to the digital vector format. The generated contours of signals were presented as time series and converted into digital format (mat files) which indicated information on ground motion signals contained in analog seismograms. We performed the quality control of the digitised traces in Python to evaluate the discriminating functionality of seismic signals by DigitSeis. We shown a robust approach of DigitSeis as a powerful toolset for processing analog seismic signals. The graphical visualisation of signal traces and analysis of the performed vectorisation results shown that the algorithms of data processing performed accurately and can be recommended in similar applications of seismic signal processing in future related works in geophysical research

Computer Vision Algorithms of DigitSeis for Building a Vectorised Dataset of Historical Seismograms from the Archive of Royal Observatory of Belgium

Archived seismograms recorded in the 20th century present a valuable source of information for monitoring earthquake activity. However, old data, which are only available as scanned paper-based images should be digitised and converted from raster to vector format prior to reuse for geophysical modelling. Seismograms have special characteristics and specific features recorded by a seismometer and encrypted in the images: signal trace lines, minute time gaps, timing and wave amplitudes. This information should be recognised and interpreted automatically when processing archives of seismograms containing large collections of data. The objective was to automatically digitise historical seismograms obtained from the archives of the Royal Observatory of Belgium (ROB). The images were originally recorded by the Galitzine seismometer in 1954 in Uccle seismic station, Belgium. A dataset included 145 TIFF images which required automatic approach of data processing. Software for digitising seismograms are limited and many have disadvantages. We applied the DigitSeis for machine-based vectorisation and reported here a full workflow of data processing. This included pattern recognition, classification, digitising, corrections and converting TIFFs to the digital vector format. The generated contours of signals were presented as time series and converted into digital format (mat files) which indicated information on ground motion signals contained in analog seismograms. We performed the quality control of the digitised traces in Python to evaluate the discriminating functionality of seismic signals by DigitSeis. We shown a robust approach of DigitSeis as a powerful toolset for processing analog seismic signals. The graphical visualisation of signal traces and analysis of the performed vectorisation results shown that the algorithms of data processing performed accurately and can be recommended in similar applications of seismic signal processing in future related works in geophysical research

Computer Vision Algorithms of DigitSeis for Building a Vectorised Dataset of Historical Seismograms from the Archive of Royal Observatory of Belgium

Archived seismograms recorded in the 20th century present a valuable source of information for monitoring earthquake activity. However, old data, which are only available as scanned paper-based images should be digitised and converted from raster to vector format prior to reuse for geophysical modelling. Seismograms have special characteristics and specific featuresrecorded by a seismometer and encrypted in the images: signal trace lines, minute time gaps, timing and wave amplitudes. This information should be recognised and interpreted automatically when processing archives of seismograms containing large collections of data. The objective was to automatically digitise historical seismograms obtained from the archives of the Royal Observatory of Belgium (ROB). The images were originallyrecorded by the Galitzine seismometer in 1954 in Uccle seismic station, Belgium. A dataset included 145 TIFF images which required automatic approach of data processing. Software for digitising seismograms are limited and many have disadvantages. We applied the DigitSeis for machine-based vectorisation and reported here a full workflowof data processing. This included pattern recognition, classification, digitising, corrections and converting TIFFs to the digital vector format. The generated contours of signals were presented as time series and converted into digital format (mat files) which indicated information on ground motion signals contained in analog seismograms. We performed the quality control of the digitised traces in Python to evaluate the discriminating functionality of seismic signals by DigitSeis. We shown a robust approach of DigitSeis as a powerful toolset for processing analog seismic signals. The graphical visualisation of signal traces and analysis of the performed vectorisation results shown that the algorithms of data processing performed accurately and can be recommended in similar applications of seismic signal processing in future related works in geophysical research

New insights into the Kawah Ijen hydrothermal system from geophysical data

The magmatic–hydrothermal system of Kawah Ijen volcano is one of the most exotic on Earth, featuring the largest acidic lake on the planet, a hyper-acidic river and a passively degassing silicic dome. While previous studies have mostly described this unique system from a geochemical perspective, to date there has been no comprehensive geophysical investigation of the system. In our study, we surveyed the lake using a thermocouple, a thermal camera, an echo sounder and CO2 sensors. Furthermore, we gained insights into the hydrogeological structures by combining self-potential surveys with ground and water temperatures. Our results show that the hydrothermal system is self-sealed within the upper edifice and releases pressurized gas only through the active crater. We also show that the extensive hydrological system is formed by not one but three aquifers: a south aquifer that seems to be completely isolated, a west aquifer that sustains the acidic upper springs, and an east aquifer that is the main source of fresh water for the lake. In contrast with previous research, we emphasize the heterogeneity of the acidic lake, illustrated by intense subaqueous degassing. These findings provide new insights into this unique, hazardous hydrothermal system, which may eventually improve the existing monitoring system

Reversal of tumoral immune resistance by inhibition of tryptophan 2,3-dioxygenase.

Tryptophan catabolism mediated by indoleamine 2,3-dioxygenase (IDO1) is an important mechanism of peripheral immune tolerance contributing to tumoral immune resistance, and IDO1 inhibition is an active area of drug development. Tryptophan 2,3-dioxygenase (TDO) is an unrelated hepatic enzyme that also degrades tryptophan along the kynurenine pathway. Here, we show that enzymatically active TDO is expressed in a significant proportion of human tumors. In a preclinical model, TDO expression by tumors prevented their rejection by immunized mice. We developed a TDO inhibitor, which, upon systemic treatment, restored the ability of mice to reject TDO-expressing tumors. Our results describe a mechanism of tumoral immune resistance based on TDO expression and establish proof-of-concept for the use of TDO inhibitors in cancer therapy