ALBERT

Description: Millions of tons of plastic waste are released into the marine environment every year. While they steadily accumulate, synthetic polymers provide a habitat for microorganisms. This denominated Plastisphere has been studied in detail over the past ten years. So have the enzymes responsible for microbial degradation, which are unfortunately lacking for most sorts of plastics. Therefore, the BMBF-funded project PLASTISEA is focusing on bioprospecting the marine treasure trove for novel plastic acting enzymes.

Description: Many of the socio-economic and environmental challenges of the 21st century like the growing energy and food demand, rising sea levels and temperatures put stress on marine ecosystems and coastal populations. This requires a significant strengthening of our monitoring capacities for processes in the water column, at the seafloor and in the subsurface. However, present-day seafloor instruments and the required infrastructure to operate these are expensive and inaccessible. We envision a future Internet of Underwater Things, composed of small and cheap but intelligent underwater nodes. Each node will be equipped with sensing, communication, and computing capabilities. Building on distributed event detection and cross-domain data fusion, such an Internet of Underwater Things will enable new applications. In this paper, we argue that to make this vision a reality, we need new methodologies for resource-efficient and distributed cross-domain data fusion. Resource-efficient, distributed neural networks will serve as data-analytics pipelines to derive highly aggregated patterns of interest from raw data. These will serve as (1) a common base in time and space for fusion of heterogeneous data, and (2) be sufficiently small to be transmitted efficiently in resource-constrained settings.

Description: Die Messung submariner Bodendeformationen an den Flanken von Inselvulkanen hilft dabei, ihre Stabilität und die Gefahr von Hangrutschungen einzuschätzen, ist aber inherent schwierig für Gebiete, die unter Wasser liegen. Wiederholte Seismik- oder Fächerecholot-Vermessungen können größere Gebiete abdecken, aber Auflösung und Lokalisierung sind bestimmten Grenzen unterworfen. Optische Daten andererseits sind besser aufgelöst, aber limitiert in ihrer räumlichen Abdeckung, und Meeresbodengeodäsie wiederum liefert nur punktuelle Information. In diesem Artikel schlagen wir vor, verschiedene Arten von Fernerkundungsdaten zusammenzubringen und auch mit bestehenden statischen und dynamischen Modellen zu verschneiden. Aufgrund ihrer verschiedenen Modalitäten, Unsicherheiten und Skalierungen ist dies jedoch schwierig und bedarf einer Fusion. Zusammen mit anderen Aspekten (Erdbeben, Strömungen etc.) sollen die fusionierten Daten und Modelle langfristig neue Einblicke in das dynamische System des sich verändernden Meeresbodens, die dafür verantwortlichen Faktoren sowie die Auswirkungen instabiler submariner Hänge auf andere Meeressysteme bieten.

Description: A central promise of cross-domain fusion (CDF) is the provision of a “bigger picture” that integrates different disciplines and may span very different levels of detail. We present a number of settings that call for this bigger picture, with a particular focus on how information from several domains can be made easily accessible and visualizable for different stakeholders. We propose harnessing an approach that is now well established in interactive maps, which we refer to as the “Google maps approach” (Google LLC, Mountain View, CA, USA), which combines effective filtering with intuitive user interaction. We expect this approach to be applicable to a range of CDF settings.

Description: Consistently high data quality is essential for the development of novel loss functions and architectures in the field of deep learning. The existence of such data and labels is usually presumed, while acquiring high-quality datasets is still a major issue in many cases. Subjective annotations by annotators often lead to ambiguous labels in real-world datasets. We propose a data-centric approach to relabel such ambiguous labels instead of implementing the handling of this issue in a neural network. A hard classification is by definition not enough to capture the real-world ambiguity of the data. Therefore, we propose our method “Data-Centric Classification & Clustering (DC3)” which combines semi-supervised classification and clustering. It automatically estimates the ambiguity of an image and performs a classification or clustering depending on that ambiguity. DC3 is general in nature so that it can be used in addition to many Semi-Supervised Learning (SSL) algorithms. On average, our approach yields a 7.6% better F1-Score for classifications and a 7.9% lower inner distance of clusters across multiple evaluated SSL algorithms and datasets. Most importantly, we give a proof-of-concept that the classifications and clusterings from DC3 are beneficial as proposals for the manual refinement of such ambiguous labels. Overall, a combination of SSL with our method DC3 can lead to better handling of ambiguous labels during the annotation process. (Source code is available at https://github.com/Emprime/dc3).

Description: The gas hydrate system off Mauritania is characterized by the undulating landward termination of a gas hydrate-related bottom simulating reflector (BSR). Some of the most landward sections of this BSR reach up to within 6 m of the seafloor. This suggests a shallow sulphate-methane-interface over an unusually large area. We attribute this to the presence of large amounts of methane due to the efficient burial of organic matter in a high-productivity oceanographic region, and the efficient channelling of methane along permeable turbidite beds towards the feather edge of the gas hydrate stability zone. This is consistent with the observation of steps in the BSR, where it cross-cuts other inferred permeable horizons. The high thermal conductivity of a salt dome in the southern part of the study area distorts the subsurface temperature field, giving the base of the hydrate stability zone a concave-down shape. Within this anticline of the BSR, high amplitudes and a horizontal reflection that crosses the sedimentary strata indicate the entrapment of free gas. We interpret this as a direct indication of a reduced hydraulic permeability of the hydrate-bearing sediment.

Description: Spectacular advances have been made in the field of machine vision over the past decade. While this discipline is traditionally driven by geometric models, neural networks have proven to be superior in some applications and have significantly expanded the limits of what is possible. At the same time, conventional graphic models describe the relationship between images and the associated scene with textures and light in a physically realistic manner and are an important part of photogrammetry. Differential renderers combine these approaches by enabling gradient-based optimization in fixed structures of a graphics pipeline and thus adapt the learning process of neural networks. This fusion of formalized knowledge and machine learning motivates the idea of a modular differentiable renderer in which physical and statistical models can be recombined depending on the use case. We therefore present Gemini Connector: an initiative for the modular development and combination of differentiable physical models and neural networks. We examine opportunities and problems and motivate the idea with the extension of a differentiable rendering pipeline to include models of underwater optics for the analysis of deep sea images. Finally, we discuss use cases, especially within the Cross-Domain Fusion initiative.

Description: Interactive exploration of Earth system simulations may have great potential to improve the scientific modeling process. It will allow monitoring of the state of the simulation via dashboards presenting real-time diagnostics within a digital twin world. We present the state of the art for Earth system modeling in this context. Cross-domain data handling and fusion will make it possible to integrate model and observation data in the context of digital twins of the ocean. Domain-driven modularization of monolithic Earth system models allows one to recover interfaces for such a cross-domain fusion. Reverse engineering with static and dynamic analysis enables modularization of Earth system models. The modularization does not only help with restructuring existing Earth system models, it also makes it possible to integrate additional scientific domains into the interactive simulation environment.

Description: Well-constrained and widely distributed bottom simulating reflectors in various geological settings across both passive and active margins make the area offshore southwestern Taiwan an excellent location to study gas hydrate dynamics and fluid flow systems. Seismic data reveal the presence of subsurface fluid flow systems and ubiquitous free gas and gas hydrates. This article aims to summarize and map the different types of seismic observations related to the gas hydrate system. The spatial distribution of seismic indicators for gas accumulation, fluid migration, and the presence of gas hydrates suggests that topographic highs on both passive and active margins are sites of particularly efficient free gas accumulation and gas hydrate formation. Seismic indicators observed in fold and thrust structures suggest that the fluid system in the active margin is structurally controlled and that the highest gas hydrate saturation levels are found in the cores of thrust anticlines on the lower slope of the active margin area.

Description: This article reviews extensive geophysical survey data, ocean drilling results and long-term seafloor monitoring that constrain the distribution and concentration of gas hydrates within the accretionary prism of the northern Cascadia subduction margin, located offshore Vancouver Island in Canada. Seismic surveys and geologic studies conducted since the 1980s have mapped the bottom simulating reflector (BSR), detected gas hydrate occurrence and estimated gas hydrate and free gas concentrations. Additional constraints were obtained from seafloor-towed, controlled-source electromagnetic surveying. A component of these studies has been the examination of low-temperature seafloor vents and seeps that emit gas and fluids into the ocean. These features are identified seismically as chimney-like zones of reduced acoustic reflectivity within the sediment stratigraphy, functioning as conduits for gas and fluid migration from below the BSR to the seafloor. Gas hydrates have been recovered from the seafloor and from sediment cores at vent sites, mostly in massive (nodular) form and as a vein-like fracture filling. The Ocean Networks Canada cabled NEPTUNE observatory has gathered extensive continuous, long-term observations on gas hydrate dynamics at the seafloor and in boreholes at two nodes on the continental slope featuring high gas hydrate concentrations. Measurements taken at the observatory include a time-series of gas bubble emission rates, changes in the near-seafloor electromagnetic structure and seafloor compliance linked to gas hydrate formation and dissociation. Two Integrated Ocean Drilling Program (IODP) expeditions collected cores, measured downhole properties and deployed downhole instruments within the central accretionary prism. At IODP Site U1364, pore pressures are being monitored above and below the base of the gas hydrate stability zone at a slope setting using an “Advanced Circulation Obviation Retrofit Kit” (A-CORK). Downhole pore pressures, temperatures and electrical resistivities also are being monitored at IODP Site U1416 using the “Simple Cabled Instrument for Measuring Parameters In Situ” (SCIMPI) tool at a vent site from near-seafloor to just above the base of the gas hydrate stability zone.