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The potential of weather radar observations for hydrological and meteorological research and applications is undisputed, particularly with increasing world-wide radar coverage. However, several barriers impede the use of weather radar data. These barriers are of both scientific and technical nature. The former refers to inherent measurement errors and artefacts, the latter to aspects such as reading specific data formats, geo-referencing, visualisation. The radar processing library wradlib is intended to lower these barriers by providing a free and open source tool for the most important steps in processing weather radar data for hydro-meteorological and hydrological applications. Moreover, the community-based development approach of wradlib allows scientists to share their knowledge about efficient processing algorithms and to make this knowledge available to the weather radar community in a transparent, structured and well-documented way.
Weather radar analysis has become increasingly sophisticated over the past 50 years, and efforts to keep software up to date have generally lagged behind the needs of the users. We argue that progress has been impeded by the fact that software has not been developed and shared as a community.
Recently, the situation has been changing. In this paper, the developers of a number of open-source software (OSS) projects highlight the potential of OSS to advance radar-related research. We argue that the community-based development of OSS holds the potential to reduce duplication of efforts and to create transparency in implemented algorithms while improving the quality and scope of the software. We also conclude that there is sufficiently mature technology to support collaboration across different software projects. This could allow for consolidation toward a set of interoperable software platforms, each designed to accommodate very specific user requirements.
Enzymatic hydrolysis holds great promise for plastic waste recycling and upcycling.
The interfacial catalysis mode, and the variability of polymer specimen properties under different degradation conditions, add to the complexity and difficulty of understanding polymer cleavage and engineering better biocatalysts.
We present a systemic approach to studying the enzyme-catalyzed surface erosion of poly(ethylene terephthalate) (PET) while monitoring/controlling operating conditions in real time with simultaneous detection of mass loss and changes in viscoelastic behavior.
PET nanofilms placed on water showed a porous morphology and a thicknessdependent glass transition temperature (T-g) between 40 degrees C and 44 degrees C, which is >20 degrees C lower than the T-g of bulk amorphous PET.
Hydrolysis by a dual-enzyme system containing thermostabilized variants of Ideonella sakaiensis PETase and MHETase resulted in a maximum depolymerization of 70% in 1 h at 50 degrees C.
We demonstrate that increased accessible surface area, amorphization, and T-g reduction speed up PET degradation while simultaneously lowering the threshold for degradation-induced crystallization.