Statistical Assessment of Sustainable Urban Water Ecosystems

The integrated character of Sustainable Development Goals (SDGs) reflects interconnectedness of water systems and their rich biodiversity, supplying communities with foods, clean water and air, mineral resources, and regulating their welfare and economic growth. The increasing awareness of the importance of public access to water ecosystems can have a positive impact on these ecosystems and encourage partnerships to responsible management of these resources and reactions on water crises through improvements of skills and competencies. The article highlights that the development of partnership relations for the achievement of SDGs is a target 17 of SDGs. An assessment of global and national objectives and indicators laid in the basis of the assessment of a progress on the way to the sustainable environmental accounting and the development of urban water ecosystems is given. It should be noted that the statistical information in divided into four groups which data are used in monitoring of the green economy performance: statistical base of nature assets; environmental and resource productivity of economy; environmental quality of life; economic capabilities and political reactions. The analysis showed the importance of the environmental inclusion of respective spatial groups. Aggregations based on drainage basin or ecosystem can provide better understanding of the environmental dimension of many interconnections defined for sweet water and seawater ecosystems. It is expected, however, that the applicable methods and tools will be elaborated in parallel, to simplify data use by politicians. A deeper understanding of interconnections of SDGs will enable for enhancing the efficiency of political measures.  It is concluded that the sustainable development and the 2030 Agenda for Sustainable Development can be achieved only by implementing the overall sectoral approach that will combine the tendencies of the indicators related with the environment with robust policy analysis. This requires the cohesion of all the sustainable development policy dimensions on the basis of the integrated approach, to ensure the elaboration of complementary strategies and to avoid compromises

A Targeted Sampling Strategy for Compressive Cryo Focused Ion Beam Scanning Electron Microscopy

Cryo Focused Ion-Beam Scanning Electron Microscopy (cryo FIB-SEM) enables three-dimensional and nanoscale imaging of biological specimens via a slice and view mechanism. The FIB-SEM experiments are, however, limited by a slow (typically, several hours) acquisition process and the high electron doses imposed on the beam sensitive specimen can cause damage. In this work, we present a compressive sensing variant of cryo FIB-SEM capable of reducing the operational electron dose and increasing speed. We propose two Targeted Sampling (TS) strategies that leverage the reconstructed image of the previous sample layer as a prior for designing the next subsampling mask. Our image recovery is based on a blind Bayesian dictionary learning approach, i.e., Beta Process Factor Analysis (BPFA). This method is experimentally viable due to our GPU-based implementation of BPFA. Simulations on artificial compressive FIB-SEM measurements validate the success of proposed methods: the operational electron dose can be reduced by up to 20 times. These methods have large implications for the cryo FIB-SEM community, in which the imaging of beam sensitive biological materials without beam damage is crucial