Numerische Methoden für marine biogeochemische Modelle

Marine ecosystem models are an indispensable component in the forecast of climate change. CO2 is the major anthropogenic greenhouse gas which substantially determines global warming. As an essential component of the global carbon cycle, the marine ecosystem absorbs atmospheric CO2 and, hence, slows down global warming. More specifically, the marine ecosystem stores the CO2 over a long time period, for example by fixing it through biogeochemical conversion processes. Marine ecosystem models facilitate the simulation of the marine ecosystem and, thus, the research of different processes in this ecosystem and a forecast of the evolution of the marine ecosystem. Owing to a high computational effort, the simulation of marine ecosystem models is limited by the available computing power, even on high-performance computers. To reduce the computational effort for the computation of a steady annual cycle for a marine ecosystem model, this thesis comprises the investigation of the reduction of the computational effort by using larger time steps and by predicting the steady annual cycle by means of an artificial neural network. To apply the time step always as large as possible without relying on any manual selection, two methods based on the automatic time step adjustment during the simulation are presented. The prediction of an artificial neural network served as an initial concentration for an additional simulation because the accuracy of the prediction was insufficient. These approaches, in particular, lowered the computational effort with a tolerable loss of accuracy. By the use of the surrogate-based optimization, the approaches to reduce the computational effort were applied for a parameter identification which optimizes the model parameters to adapt the marine ecosystem model output to observational data. This optimization yielded parameters close to the target ones and lowered the computational effort clearly.Marine Ökosystemmodelle sind ein unverzichtbarer Bestandteil zur Vorhersage des Klimawandels. Die globale Erwärmung wird im Wesentlichen durch Emissionen des bedeutendsten anthropogenen Treibhausgases Kohlenstoffdioxid (CO2) bestimmt. Als eine zentrale Komponente des globalen Kohlenstoffkreislaufs absorbiert das marine Ökosystem atmosphärisches CO2 und verlangsamt so die globale Erwärmung. Marine Ökosystemmodelle ermöglichen die Simulation und somit die Erforschung verschiedener Prozesse innerhalb des marinen Ökosystems sowie eine Vorhersage der zu erwartenden Entwicklung. Allerdings erfordert eine solche Simulation einen immensen Rechenaufwand und unterliegt selbst auf Hochleistungsrechnern durch die begrenzte Rechenleistung erheblichen Einschränkungen. Für die Berechnung einer jährlich periodischen Lösung des marinen Ökosystemmodells zeigt diese Arbeit Wege zur Reduktion des Rechenaufwands durch die Verwendung größerer Zeitschritte und durch die Vorhersage eines neuronalen Netzes auf. Es werden zwei Methoden vorgestellt, die auf der automatischen Anpassung des Zeitschritts während der Simulation basieren, um ohne manuelle Wahl immer den größtmöglichen Zeitschritt zu verwenden. Die Vorhersage der periodischen Lösung mit Hilfe eines neuronalen Netzes diente als Anfangskonzentration für eine zusätzliche Simulation, da die Genauigkeit der Vorhersage unzureichend war. Beide Ansätze verringerten den Rechenaufwand bei einem tolerierbaren Genauigkeitsverlust. Die Konzepte zur Reduktion des Rechenaufwands wurden für eine Parameteroptimierung mit der surrogat-basierten Optimierung verwendet, die die Modellparameter zur Anpassung des marinen Ökosystemmodells an Beobachtungsdaten optimiert. Diese Optimierung lieferte nahezu die anvisierten Parameter und verringerte den Rechenaufwand

The effect of heterogeneity on decorrelation mechanisms in spiking neural networks: a neuromorphic-hardware study

High-level brain function such as memory, classification or reasoning can be realized by means of recurrent networks of simplified model neurons. Analog neuromorphic hardware constitutes a fast and energy efficient substrate for the implementation of such neural computing architectures in technical applications and neuroscientific research. The functional performance of neural networks is often critically dependent on the level of correlations in the neural activity. In finite networks, correlations are typically inevitable due to shared presynaptic input. Recent theoretical studies have shown that inhibitory feedback, abundant in biological neural networks, can actively suppress these shared-input correlations and thereby enable neurons to fire nearly independently. For networks of spiking neurons, the decorrelating effect of inhibitory feedback has so far been explicitly demonstrated only for homogeneous networks of neurons with linear sub-threshold dynamics. Theory, however, suggests that the effect is a general phenomenon, present in any system with sufficient inhibitory feedback, irrespective of the details of the network structure or the neuronal and synaptic properties. Here, we investigate the effect of network heterogeneity on correlations in sparse, random networks of inhibitory neurons with non-linear, conductance-based synapses. Emulations of these networks on the analog neuromorphic hardware system Spikey allow us to test the efficiency of decorrelation by inhibitory feedback in the presence of hardware-specific heterogeneities. The configurability of the hardware substrate enables us to modulate the extent of heterogeneity in a systematic manner. We selectively study the effects of shared input and recurrent connections on correlations in membrane potentials and spike trains. Our results confirm ...Comment: 20 pages, 10 figures, supplement

Measurement and Modeling of a Cargo Bicycle Tire for Vehicle Dynamics Simulation

In the field of inner-city cargo transportation, solutions such as electrified cargo trailers are increasingly being used. To provide an intelligent drivetrain control system that improves driving dynamics and enables safety, it is necessary to know the characteristics of the trailer system. This includes the behavior of the tires. Existing investigations of bicycle tires focus on camber-angle-dependent models. However, in most trailers, a rigid mounting of the tires without camber is used. For this reason, a bicycle tire model is created within the scope of this study using real measurement data that represent a 20 in tire with typical wheel loads and without camber. The measurements were collected with the mobile tire measurement laboratory of the Bern University of Applied Sciences on an asphalt test site under real conditions. Crosstalk occurring in the measurement hub during the data collection was successfully corrected using a matrix method. With help of the so-called Magic Formula, a tire model was created that can be used for driving dynamics simulations and controller design

Effective decrease of photoelectric emission threshold from gold plated surfaces

Many applications require charge neutralisation of isolated test bodies and this has been successfully done using photoelectric emission from surfaces which are electrically benign(gold) or superconducting (niobium). Gold surfaces nominally have a high work function ($\sim 5.1$\,eV)which should require deep UV photons for photoemission. In practice it has been found that it can be achieved with somewhat lower energy photons with indicative work functions of ($4.1-4.3$\,eV). A detailed working understanding of the process is lacking and this work reports on a study of the photoelectric emission properties of 4.6x4.6 cm^2 gold plated surfaces, representative of those used in typical satellite applications with a film thickness of 800 nm, and measured surface roughnesses between 7 and 340 nm. Various UV sources with photon energies from 4.8 to 6.2 eV and power outputs from 1 nW to 1000 nW, illuminated a ~0.3 cm^2 of the central surface region at angles of incidence from 0 to 60 degrees. Final extrinsic quantum yields in the range 10 ppm to 44 ppm were reliably obtained during 8 campaigns, covering a ~3 year period, but with intermediate long-term variations lasting several weeks and, in some cases, bake-out procedures at up to 200 C. Experimental results were obtained in a vacuum system with a baseline pressure of ~10^{-7} mbar at room temperature. A working model, designed to allow accurate simulation of any experimental configuration, is proposed.Comment: 35 pages, 12 figure

Integrated tool chain for model-based design of Cyber-Physical Systems : The INTO-CPS project

We describe INTO-CPS, a project that aims to realise the goal of integrated tool chains for the collaborative and multidisciplinary engineering of dependable Cyber-Physical Systems (CPSs). Challenges facing model-based CPS engineering are described, focussing on the semantic diversity of models, management of the large space of models and artefacts produced in CPS engineering, and the need to evaluate effectiveness in industrial settings. We outline the approach taken to each of these issues, particularly on the use of semantically integrated multi-models, links to architectural modelling, code generation and testing, and evaluation via industry-led studies. We describe progress on the development of a prototype tool chain from baseline tools, and discuss ongoing challenges and open research questions in this area

Toward a Comprehensive and Integrated Strategy of the European Marine Research Infrastructures for Ocean Observations

Research Infrastructures (RIs) are large-scale facilities encompassing instruments, resources, data and services used by the scientific community to conduct high-level research in their respective fields. The development and integration of marine environmental RIs as European Research Vessel Operators [ERVO] (2020) is the response of the European Commission (EC) to global marine challenges through research, technological development and innovation. These infrastructures (EMSO ERIC, Euro-Argo ERIC, ICOS-ERIC Marine, LifeWatch ERIC, and EMBRC-ERIC) include specialized vessels, fixed-point monitoring systems, Lagrangian floats, test facilities, genomics observatories, bio-sensing, and Virtual Research Environments (VREs), among others. Marine ecosystems are vital for life on Earth. Global climate change is progressing rapidly, and geo-hazards, such as earthquakes, volcanic eruptions, and tsunamis, cause large losses of human life and have massive worldwide socio-economic impacts. Enhancing our marine environmental monitoring and prediction capabilities will increase our ability to respond adequately to major challenges and efficiently. Collaboration among European marine RIs aligns with and has contributed to the OceanObs’19 Conference statement and the objectives of the UN Decade of Ocean Science for Sustainable Development (2021–2030). This collaboration actively participates and supports concrete actions to increase the quality and quantity of more integrated and sustained observations in the ocean worldwide. From an innovation perspective, the next decade will increasingly count on marine RIs to support the development of new technologies and their validation in the field, increasing market uptake and produce a shift in observing capabilities and strategies.Peer reviewe

Effects of Short Term Adiponectin Receptor Agonism on Cardiac Function and Energetics in Diabetic db/db Mice.

Objective Impaired cardiac efficiency is a hallmark of diabetic cardiomyopathy in models of type 2 diabetes. Adiponectin receptor 1 (AdipoR1) deficiency impairs cardiac efficiency in non-diabetic mice, suggesting that hypoadiponectinemia in type 2 diabetes may contribute to impaired cardiac efficiency due to compromised AdipoR1 signaling. Thus, we investigated whether targeting cardiac adiponectin receptors may improve cardiac function and energetics, and attenuate diabetic cardiomyopathy in type 2 diabetic mice. Methods A non-selective adiponectin receptor agonist, AdipoRon, and vehicle were injected intraperitoneally into Eight-week-old db/db or C57BLKS/J mice for 10 days. Cardiac morphology and function were evaluated by echocardiography and working heart perfusions. Results Based on echocardiography, AdipoRon treatment did not alter ejection fraction, left ventricular diameters or left ventricular wall thickness in db/db mice compared to vehicle-treated mice. In isolated working hearts, an impairment in cardiac output and efficiency in db/db mice was not improved by AdipoRon. Mitochondrial respiratory capacity, respiration in the presence of oligomycin, and 4-hydroxynonenal levels were similar among all groups. However, AdipoRon induced a marked shift in the substrate oxidation pattern in db/db mice towards increased reliance on glucose utilization. In parallel, the diabetes-associated increase in serum triglyceride levels in vehicle-treated db/db mice was blunted by AdipoRon treatment, while an increase in myocardial triglycerides in vehicle-treated db/db mice was not altered by AdipoRon treatment. Conclusion AdipoRon treatment shifts myocardial substrate preference towards increased glucose utilization, likely by decreasing fatty acid delivery to the heart, but was not sufficient to improve cardiac output and efficiency in db/db mice

Platelet Function in Acute Experimental Pancreatitis

Acute pancreatitis (AP) is characterized by disturbances of pancreatic microcirculation. It remains unclear whether platelets contribute to these perfusion disturbances. The aim of our study was to investigate platelet activation and function in experimental AP. Acute pancreatitis was induced in rats: (1) control (n = 18; Ringer’s solution), (2) mild AP (n = 18; cerulein), and (3) severe AP (n = 18; glycodeoxycholic acid (GDOC) + cerulein). After 12 h, intravital microscopy was performed. Rhodamine-stained platelets were used to investigate velocity and endothelial adhesion in capillaries and venules. In addition, erythrocyte velocity and leukocyte adhesion were evaluated. Serum amylase, thromboxane A2, and histology were evaluated after 24 h in additional animals of each group. Results showed that 24 h after cerulein application, histology exhibited a mild AP, whereas GDOC induced severe necrotizing AP. Intravital microscopy showed significantly more platelet–endothelium interaction, reduced erythrocyte velocity, and increased leukocyte adherence in animals with AP compared to control animals. Thromboxane levels were significantly elevated in all AP animals and correlated with the extent of platelet activation and severity of AP. In conclusion, platelet activation plays an important role in acute, especially necrotizing, pancreatitis. Mainly temporary platelet–endothelium interaction is observed during mild AP, whereas severe AP is characterized by firm adhesion with consecutive coagulatory activation and perfusion failure