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  • Weitere Quellen  (303)
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  • 1
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    Marine Mikroorganismen für den Plastikabbau (2022)
    Springer
    Details
    Publikationsdatum: 2023-01-04
    Beschreibung: 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.
    Materialart: Article , PeerReviewed
    Format: text
    Standort Signatur Erwartet Verfügbarkeit
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    ARTIKEL (OCEANREP)
  • 2
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    Cross-domain fusion in smart seafloor sensor networks (2022)
    Springer
    Details
    Publikationsdatum: 2023-01-04
    Beschreibung: 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.
    Materialart: Article , PeerReviewed
    Format: text
    Standort Signatur Erwartet Verfügbarkeit
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    ARTIKEL (OCEANREP)
  • 3
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    Fusion seismischer, akustischer und optischer Unterwasserdaten und Modelle zur Analyse submariner Hangrutschungen an Vulkansystemen (2022)
    Springer
    Details
    Publikationsdatum: 2023-01-04
    Beschreibung: 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.
    Materialart: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    Standort Signatur Erwartet Verfügbarkeit
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  • 4
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    The Marine Biodiversity Observation Network Plankton Workshops: Plankton Ecosystem Function, Biodiversity, and Forecasting - Research Requirements and Applications (2022)
    ASLO (Association for the Sciences of Limnology and Oceanography) | Wiley
    Details
    Publikationsdatum: 2023-01-04
    Beschreibung: Plankton is a massive and phylogenetically diverse group of thousands of prokaryotes, protists (unicellular eukaryotic organisms), and metazoans (multicellular eukaryotic organisms; Fig. 1). Plankton functional diversity is at the core of various ecological processes, including productivity, carbon cycling and sequestration, nutrient cycling (Falkowski 2012), interspecies interactions, and food web dynamics and structure (D'Alelio et al. 2016). Through these functions, plankton play a critical role in the health of the coastal and open ocean and provide essential ecosystem services. Yet, at present, our understanding of plankton dynamics is insufficient to project how climate change and other human-driven impacts affect the functional diversity of plankton. That limits our ability to predict how critical ecosystem services will change in the future and develop strategies to adapt to these changes.
    Materialart: Article , PeerReviewed
    Format: text
    Standort Signatur Erwartet Verfügbarkeit
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  • 5
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    Getting the big picture in cross-domain fusion (2022)
    Springer
    Details
    Publikationsdatum: 2023-01-04
    Beschreibung: 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.
    Materialart: Article , PeerReviewed
    Format: text
    Standort Signatur Erwartet Verfügbarkeit
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  • 6
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    A Data-Centric Approach for Improving Ambiguous Labels with Combined Semi-supervised Classification and Clustering (2022)
    Springer
    Details
    Publikationsdatum: 2023-01-02
    Beschreibung: 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).
    Materialart: Book chapter , NonPeerReviewed
    Format: text
    Standort Signatur Erwartet Verfügbarkeit
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  • 7
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    Wissen kompakt, Künstlicher Auftrieb: Mehr Power für die biologische Kohlenstoffpumpe des Meeres (2023)
    CDRmare Research Mission
    Details
    Publikationsdatum: 2023-01-09
    Beschreibung: Algen, Zooplankton und Fische gehören zu den Schlüsselakteuren der biologischen Kohlenstoffpumpe, mithilfe derer der Ozean der Atmosphäre auf natürliche Weise Kohlendioxid entnimmt und den enthaltenen Kohlenstoff in großen Wassertiefen einlagert. Damit dieser Mechanismus jedoch optimal funktioniert, braucht es Nährstoffe, die vielerorts fehlen, zumindest im lichtdurchfluteten Oberflächenwasser. Durch das Heraufpumpen nährstoffreichen Tiefenwassers könnte der Mensch diesen Nährstoffmangel beheben. Ob ein solcher künstlicher Auftrieb aber tatsächlich klimawirksam wäre, welche Risiken er mit sich brächte und ob er technisch und rechtlich im großen Stil umgesetzt werden könnte, ist bislang ungewiss. Die Forschungsmission CDRmare liefert Antworten.
    Materialart: Report , NonPeerReviewed
    Format: text
    Standort Signatur Erwartet Verfügbarkeit
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  • 8
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    Activity-Based Screening of Metagenomic Fosmid Libraries for Hydrogen-Uptake Enzymes (2023)
    Springer
    Details
    Publikationsdatum: 2023-01-19
    Beschreibung: Here, we outline how to identify hydrogenase enzymes from metagenomic fosmid libraries through an activity-based screening approach. A metagenomic fosmid library is constructed in E. coli and the fosmids are transferred into a hydrogenase deletion mutant of Shewanella oneidensis MR-1 (ΔhyaB) via triparental mating. If a fosmid clone exhibits hydrogen-uptake activity, S. oneidensis’ phenotype is restored and hydrogenase activity is indicated by a color change of the medium from yellow to colorless. The screen enables screening of 48 metagenomic fosmid clones in parallel.
    Materialart: Book chapter , NonPeerReviewed , info:eu-repo/semantics/bookPart
    Standort Signatur Erwartet Verfügbarkeit
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  • 9
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    Insights into Gas Hydrate Dynamics from 3D Seismic Data, Offshore Mauritania (2022)
    Springer
    Details
    Publikationsdatum: 2023-01-19
    Beschreibung: 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.
    Materialart: Book chapter , NonPeerReviewed
    Format: text
    Standort Signatur Erwartet Verfügbarkeit
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  • 10
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    Gemini connector: Interfacing differentiable physical models and neural networks (2022)
    Springer
    Details
    Publikationsdatum: 2023-01-24
    Beschreibung: 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.
    Materialart: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    Standort Signatur Erwartet Verfügbarkeit
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