Objektorientierte Modellierung mit Modelica zur Echtzeitsimulation und Optimierung von Antriebssträngen

In diesem Beitrag werden Methoden und Werkzeuge zur Automatischen Applikation elektronischer Getriebesteuergeräte und deren Integration beschrieben. Am Beispiel eines mit der Sprache Modelica modellierten und in Echtzeit simulierten Sechsgang-Automatikgetriebes wird gezeigt, wie die Parameter eines exemplarischen Getriebesteuergerätes mittels numerischer Optimierung verbessert werden können

\"Uber wissenschaftliche Exzellenz und Wettbewerb

The pursuit of excellence seems to be the True North of academia. What is meant by excellence? Can excellence be measured? This article discusses the concept of excellence in the context of research and competition.Comment: in German languag

Transcriptomic characterization of two major Fusarium resistance quantitative trait loci (QTLs), Fhb1 and Qfhs.ifa-5A, identifies novel candidate genes

Fusarium head blight, caused by Fusarium graminearum, is a devastating disease of wheat. We developed near-isogenic lines (NILs) differing in the two strongest known F. graminearum resistance quantitative trait loci (QTLs), Qfhs.ndsu-3BS (also known as resistance gene Fhb1) and Qfhs.ifa-5A, which are located on the short arm of chromosome 3B and on chromosome 5A, respectively. These NILs showing different levels of resistance were used to identify transcripts that are changed significantly in a QTL-specific manner in response to the pathogen and between mock-inoculated samples. After inoculation with F. graminearum spores, 16 transcripts showed a significantly different response for Fhb1 and 352 for Qfhs.ifa-5A. Notably, we identified a lipid transfer protein which is constitutively at least 50-fold more abundant in plants carrying the resistant allele of Qfhs.ifa-5A. In addition to this candidate gene associated with Qfhs.ifa-5A, we identified a uridine diphosphate (UDP)-glycosyltransferase gene, designated TaUGT12887, exhibiting a positive difference in response to the pathogen in lines harbouring both QTLs relative to lines carrying only the Qfhs.ifa-5A resistance allele, suggesting Fhb1 dependence of this transcript. Yet, this dependence was observed only in the NIL with already higher basal resistance. The complete cDNA of TaUGT12887 was reconstituted from available wheat genomic sequences, and a synthetic recoded gene was expressed in a toxin-sensitive strain of Saccharomyces cerevisiae. This gene conferred deoxynivalenol resistance, albeit much weaker than that observed with the previously characterized barley HvUGT13248

An Empirical Survey on Co-simulation: Promising Standards, Challenges and Research Needs

Co-simulation is a promising approach for the modelling and simulation of complex systems, that makes use of mature simulation tools in the respective domains. It has been applied in wildly different domains, oftentimes without a comprehensive study of the impact to the simulation results. As a consequence, over the recent years, researchers have set out to understand the essential challenges arising from the application of this technique. This paper complements the existing surveys in that the social and empirical aspects were addressed. More than 50 experts participated in a two-stage Delphi study to determine current challenges, research needs and promising standards and tools. Furthermore, an analysis of the strengths, weakness, opportunities and threats of co-simulation utilizing the analytic hierarchy process resulting in a SWOT-AHP analysis is presented. The empirical results of this study show that experts consider the FMI standard to be the most promising standard for continuous time, discrete event and hybrid co-simulation. The results of the SWOT-AHP analysis indicate that factors related to strengths and opportunities predominate

IoT Middleware Platforms for Smart Energy Systems: An Empirical Expert Survey

Middleware platforms are key technology in any Internet of Things (IoT) system, considering their role in managing the intermediary communications between devices and applications. In the energy sector, it has been shown that IoT devices enable the integration of all network assets to one large distributed system. This comes with significant benefits, such as improving energy efficiency, boosting the generation of renewable energy, reducing maintenance costs and increasing comfort. Various existing IoT middlware solutions encounter several problems that limit their performance, such as vendor locks. Hence, this paper presents a literature review and an expert survey on IoT middleware platforms in energy systems, in order to provide a set of tools and functionalities to be supported by any future efficient, flexible and interoperable IoT middleware considering the market needs. The analysis of the results shows that experts currently use the IoT middleware mainly to deploy services such as visualization, monitoring and benchmarking of energy consumption, and energy optimization is considered as a future application to target. Likewise, non-functional requirements, such as security and privacy, play vital roles in the IoT platforms’ performances

Constructing Neural Network-Based Models for Simulating Dynamical Systems

Dynamical systems see widespread use in natural sciences like physics, biology, chemistry, as well as engineering disciplines such as circuit analysis, computational fluid dynamics, and control. For simple systems, the differential equations governing the dynamics can be derived by applying fundamental physical laws. However, for more complex systems, this approach becomes exceedingly difficult. Data-driven modeling is an alternative paradigm that seeks to learn an approximation of the dynamics of a system using observations of the true system. In recent years, there has been an increased interest in data-driven modeling techniques, in particular neural networks have proven to provide an effective framework for solving a wide range of tasks. This paper provides a survey of the different ways to construct models of dynamical systems using neural networks. In addition to the basic overview, we review the related literature and outline the most significant challenges from numerical simulations that this modeling paradigm must overcome. Based on the reviewed literature and identified challenges, we provide a discussion on promising research areas

Interleukin‐6 initiates muscle‐ and adipose tissue wasting in a novel C57BL/6 model of cancer‐associated cachexia

BACKGROUND: Cancer‐associated cachexia (CAC) is a wasting syndrome drastically reducing efficacy of chemotherapy and life expectancy of patients. CAC affects up to 80% of cancer patients, yet the mechanisms underlying the disease are not well understood and no approved disease‐specific medication exists. As a multiorgan disorder, CAC can only be studied on an organismal level. To cover the diverse aetiologies of CAC, researchers rely on the availability of a multifaceted pool of cancer models with varying degrees of cachexia symptoms. So far, no tumour model syngeneic to C57BL/6 mice exists that allows direct comparison between cachexigenic‐ and non‐cachexigenic tumours. METHODS: MCA207 and CHX207 fibrosarcoma cells were intramuscularly implanted into male or female, 10–11‐week‐old C57BL/6J mice. Tumour tissues were subjected to magnetic resonance imaging, immunohistochemical‐, and transcriptomic analysis. Mice were analysed for tumour growth, body weight and ‐composition, food‐ and water intake, locomotor activity, O(2) consumption, CO(2) production, circulating blood cells, metabolites, and tumourkines. Mice were sacrificed with same tumour weights in all groups. Adipose tissues were examined using high‐resolution respirometry, lipolysis measurements in vitro and ex vivo, and radioactive tracer studies in vivo. Gene expression was determined in adipose‐ and muscle tissues by quantitative PCR and Western blotting analyses. Muscles and cultured myotubes were analysed histologically and by immunofluorescence microscopy for myofibre cross sectional area and myofibre diameter, respectively. Interleukin‐6 (Il‐6) was deleted from cancer cells using CRISPR/Cas9 mediated gene editing. RESULTS: CHX207, but not MCA207‐tumour‐bearing mice exhibited major clinical features of CAC, including systemic inflammation, increased plasma IL‐6 concentrations (190 pg/mL, P ≤ 0.0001), increased energy expenditure (+28%, P ≤ 0.01), adipose tissue loss (−47%, P ≤ 0.0001), skeletal muscle wasting (−18%, P ≤ 0.001), and body weight reduction (−13%, P ≤ 0.01) 13 days after cancer cell inoculation. Adipose tissue loss resulted from reduced lipid uptake and ‐synthesis combined with increased lipolysis but was not associated with elevated beta‐adrenergic signalling or adipose tissue browning. Muscle atrophy was evident by reduced myofibre cross sectional area (−21.8%, P ≤ 0.001), increased catabolic‐ and reduced anabolic signalling. Deletion of IL‐6 from CHX207 cancer cells completely protected CHX207(IL6KO)‐tumour‐bearing mice from CAC. CONCLUSIONS: In this study, we present CHX207 fibrosarcoma cells as a novel tool to investigate the mediators and metabolic consequences of CAC in C57BL/6 mice in comparison to non‐cachectic MCA207‐tumour‐bearing mice. IL‐6 represents an essential trigger for CAC development in CHX207‐tumour‐bearing mice

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements