The Hierarchic treatment of marine ecological information from spatial networks of benthic platforms

Measuring biodiversity simultaneously in different locations, at different temporal scales, and over wide spatial scales is of strategic importance for the improvement of our understanding of the functioning of marine ecosystems and for the conservation of their biodiversity. Monitoring networks of cabled observatories, along with other docked autonomous systems (e.g., Remotely Operated Vehicles [ROVs], Autonomous Underwater Vehicles [AUVs], and crawlers), are being conceived and established at a spatial scale capable of tracking energy fluxes across benthic and pelagic compartments, as well as across geographic ecotones. At the same time, optoacoustic imaging is sustaining an unprecedented expansion in marine ecological monitoring, enabling the acquisition of new biological and environmental data at an appropriate spatiotemporal scale. At this stage, one of the main problems for an effective application of these technologies is the processing, storage, and treatment of the acquired complex ecological information. Here, we provide a conceptual overview on the technological developments in the multiparametric generation, storage, and automated hierarchic treatment of biological and environmental information required to capture the spatiotemporal complexity of a marine ecosystem. In doing so, we present a pipeline of ecological data acquisition and processing in different steps and prone to automation. We also give an example of population biomass, community richness and biodiversity data computation (as indicators for ecosystem functionality) with an Internet Operated Vehicle (a mobile crawler). Finally, we discuss the software requirements for that automated data processing at the level of cyber-infrastructures with sensor calibration and control, data banking, and ingestion into large data portals.Peer ReviewedPostprint (published version

Design of of model-based controllers via parametric programming

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Health Fetishism Among The Nacirema: A Fugue On Jenny Reardon’s The Postgenomic Condition: Ethics, Justice, and Knowledge After The Genome (Chicago University Press, 2017) And Isabelle Stengers’ Another Science Is Possible: A Manifesto For Slow Science (Polity Press, 2018)

Personalized medicine has become a goal of genomics and of health policy makers. This article reviews two recent books that are highly critical of this approach, finding their arguments very thoughtful and important. According to Stengers, biology’s rush to become a science of genome sequences has made it part of the “speculative economy of promise.” Reardon claims that the postgenomic condition is the attempt to find meaning in all the troves of data that have been generated. The current paper attempts to extend these arguments by showing that scientific alternatives such as ecological developmental biology and the tissue organization field theory of cancer provide evidence demonstrating that genomic data alone is not sufficient to explain the origins of common disease. What does need to be explained is the intransience of medical scientists to recognize other explanatory models beside the “-omics” approaches based on computational algorithms. To this end, various notions of commodity and religious fetishism are used. This is not to say that there is no place for Big Data and genomics. Rather, these methodologies should have a definite place among others. These books suggest that Big Data genomics is like the cancer it is supposed to conquer. It has expanded unregulated and threatens to kill the body in which it arose