239 research outputs found

    Nutzung von KI-Methoden fĆ¼r die Kupplungsentwicklung in automobilen AntriebsstrƤngen = Use of AI methods for clutch development in automotive drivetrains

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    Im Spannungsfeld steigender Erwartungen an Fahrkomfort und Energieeffizienz stoƟen aktuelle Entwicklungsmethoden der Modellbildung und Optimierung fĆ¼r Fahrzeugkupplungen an ihre Grenzen. In diesem Beitrag wird der Einsatz von KI-Methoden fĆ¼r die Kupplungsentwicklung untersucht und ein Ɯberblick anhand verschiedener Anwendungsbeispiele in aktuellen Forschungsprojekten der Mercedes-Benz AG gegeben. Mittels Ć¼berwachten Lernens und tiefen neuronalen Netzen werden ein Reibungszahlmodell sowie ein Temperaturmodell einer Kupplung mit hoher AbbildungsgĆ¼te entwickelt. VerstƤrkendes Lernen mit tiefen neuronalen Netzen wird zur Synthese von Regelungen fĆ¼r verschiedene Gangwechsel eingesetzt. Fahrzeugmessdaten werden mit Cluster-Algorithmen analysiert, um Handlungsempfehlungen fĆ¼r die Applikation des Motorwiederstarts eines hybriden Antriebsstrangs abzuleiten. Mit den gezeigten Methoden steigt das Automatisierungspotential in der Entwicklung und der Aufwand fĆ¼r die Ɯbernahme komplexer Entwicklungsprozesse auf neue Getriebevarianten sinkt

    Structural Analysis to Determine the Core of Hypoxia Response Network

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    The advent of sophisticated molecular biology techniques allows to deduce the structure of complex biological networks. However, networks tend to be huge and impose computational challenges on traditional mathematical analysis due to their high dimension and lack of reliable kinetic data. To overcome this problem, complex biological networks are decomposed into modules that are assumed to capture essential aspects of the full network's dynamics. The question that begs for an answer is how to identify the core that is representative of a network's dynamics, its function and robustness. One of the powerful methods to probe into the structure of a network is Petri net analysis. Petri nets support network visualization and execution. They are also equipped with sound mathematical and formal reasoning based on which a network can be decomposed into modules. The structural analysis provides insight into the robustness and facilitates the identification of fragile nodes. The application of these techniques to a previously proposed hypoxia control network reveals three functional modules responsible for degrading the hypoxia-inducible factor (HIF). Interestingly, the structural analysis identifies superfluous network parts and suggests that the reversibility of the reactions are not important for the essential functionality. The core network is determined to be the union of the three reduced individual modules. The structural analysis results are confirmed by numerical integration of the differential equations induced by the individual modules as well as their composition. The structural analysis leads also to a coarse network structure highlighting the structural principles inherent in the three functional modules. Importantly, our analysis identifies the fragile node in this robust network without which the switch-like behavior is shown to be completely absent

    Engineering Yarrowia lipolytica to Produce Glycoproteins Homogeneously Modified with the Universal Man3GlcNAc2 N-Glycan Core

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    Yarrowia lipolytica is a dimorphic yeast that efficiently secretes various heterologous proteins and is classified as ā€œgenerally recognized as safe.ā€ Therefore, it is an attractive protein production host. However, yeasts modify glycoproteins with non-human high mannose-type N-glycans. These structures reduce the protein half-life in vivo and can be immunogenic in man. Here, we describe how we genetically engineered N-glycan biosynthesis in Yarrowia lipolytica so that it produces Man3GlcNAc2 structures on its glycoproteins. We obtained unprecedented levels of homogeneity of this glycanstructure. This is the ideal starting point for building human-like sugars. Disruption of the ALG3 gene resulted in modification of proteins mainly with Man5GlcNAc2 and GlcMan5GlcNAc2 glycans, and to a lesser extent with Glc2Man5GlcNAc2 glycans. To avoid underoccupancy of glycosylation sites, we concomitantly overexpressed ALG6. We also explored several approaches to remove the terminal glucose residues, which hamper further humanization of N-glycosylation; overexpression of the heterodimeric Apergillus niger glucosidase II proved to be the most effective approach. Finally, we overexpressed an Ī±-1,2-mannosidase to obtain Man3GlcNAc2 structures, which are substrates for the synthesis of complex-type glycans. The final Yarrowia lipolytica strain produces proteins glycosylated with the trimannosyl core N-glycan (Man3GlcNAc2), which is the common core of all complex-type N-glycans. All these glycans can be constructed on the obtained trimannosyl N-glycan using either in vivo or in vitro modification with the appropriate glycosyltransferases. The results demonstrate the high potential of Yarrowia lipolytica to be developed as an efficient expression system for the production of glycoproteins with humanized glycans

    Glycosylation Site Alteration in the Evolution of Influenza A (H1N1) Viruses

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    Influenza virus typically alters protein glycosylation in order to escape immune pressure from hosts and hence to facilitate survival in different host environments. In this study, the patterns and conservation of glycosylation sites on HA and NA of influenza A/H1N1 viruses isolated from various hosts at different time periods were systematically analyzed, by employing a new strategy combining genome-based glycosylation site prediction and 3D modeling of glycoprotein structures, for elucidation of the modes and laws of glycosylation site alteration in the evolution of influenza A/H1N1 viruses. The results showed that influenza H1N1 viruses underwent different alterations of protein glycosylation in different hosts. Two alternative modes of glycosylation site alteration were involved in the evolution of human influenza virus: One was an increase in glycosylation site numbers, which mainly occurred with high frequency in the early stages of evolution. The other was a change in the positional conversion of the glycosylation sites, which was the dominating mode with relatively low frequency in the later evolutionary stages. The mechanisms and possibly biological functions of glycosylation site alteration for the evolution of influenza A/H1N1 viruses were also discussed. Importantly, the significant role of positional alteration of glycosylation sites in the host adaptation of influenza virus was elucidated. Although the results still need to be supported by experimental data, the information here may provide some constructive suggestions for research into the glycosylation of influenza viruses as well as even the design of surveillance and the production of viral vaccines

    Simulation of Flow-Driven Adiabatic Inversion in Dual Coil Continuous ASL at 9.4 T

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    Purpose/Introduction: Continuous ASL with labeling coils placed at the subjectĀ“s neck (DC-CASL, [1]) has a high sensitivity [2], does not suffer from magnetization transfer effects and leads to lower power deposition than any other CASL technique. The latter makes it especially interesting for ultra-high field applications where the TR in ASL is limited by the high SAR evoked by the inversion. So far, simulations of the efficiency were performed for field strengths up to 3 T [2ā€“3]. However, the shorter T2 of arterial blood at 9.4 T requires reassessing of the labeling process at this field strength. Subjects and Methods: Bloch simulations were performed in Matlab for different blood velocities (vblood = 0.01 - 1 m/s), transmit fields (B1 +=2.5, 3.5 and 4.5 lT) and gradients (Gz = 0-10 mT/m) assuming T1 = 2400 ms [5], T2 = 30 ms [6] at 9.4 T. For comparison, calculations were also performed with 3 T relaxation times (T1 = 1330 s [7], T2 = 250 ms [8]). The efficiencies of cases with an adiabaticity \1 were set to zero. In order to take the temporally varying blood volume and the parabolic velocity profile into account, the total efficiency was calculated as described in Ref. [2]. Two flow weighting models were investigated: I. A two period model [2]; II. A detailed representation of vblood over time adapted from [4]. A constant transmit field was assumed since the influences of the B1 + shape of a surface coil on the inversion are negligible [3]. Results: Figure 1a shows the overall efficiencies for three transmit field strengths at 9.4 T and Fig. 1b the corresponding values at 3 T. For a given B1 +, the more detailed model II (b) requires slightly stronger gradients than model I (a) to achieve the optimal performance. The flow weighted inversion efficiency during the cardiac circle is depicted in Fig. 2. Table 1 comprises the efficiencies for some B1 +/Gz combinations. Discussion/Conclusion: In comparison to 3 T, stronger gradients are required for labeling at ultra-high field. However the lower efficiency will be compensated by the longer longitudinal relaxation time at 9.4 T. One possibility to reduce the T2 effect may be the utilization of local non-linear gradient coils [3]. The strong dependency on vblood complicates the quantification of DC-CASL especially in patients
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