Aspect-Oriented State Machines

UML state machines are a widely used language for modeling software behavior. They are considered to be simple and intuitively comprehensible, and are hence one of the most popular languages for modeling reactive components. However, this seeming ease to use vanishes rapidly as soon as the complexity of the system to model increases. In fact, even state machines modeling ``almost trivial'' behavior may get rather hard to understand and error-prone. In particular, synchronization of parallel regions and history-based features are often difficult to model in UML state machines. We therefore propose High-Level Aspect (HiLA), a new, aspect-oriented extension of UML state machines, which can improve the modularity, thus the comprehensibility and reusability of UML state machines considerably. Aspects are used to define additional or alternative system behaviors at certain ``interesting'' points of time in the execution of the state machine, and achieve a high degree of separation of concerns. The distinguishing feature of HiLA w.r.t. other approaches of aspect-oriented state machines is that HiLA aspects are defined on a high, i.e. semantic level as opposed to a low, i.e. syntactic level. This semantic approach makes \HiLA aspects often simpler and better comprehensible than aspects of syntactic approaches. The contributions of this thesis include 1) the abstract and the concrete syntax of HiLA, 2) the weaving algorithms showing how the (additional or alternative) behaviors, separately modeled in aspects, are composed with the base state machine, giving the complete behavior of the system, 3) a formal semantics for HiLA aspects to define how the aspects are activated and (after the execution) left. We also discuss what conflicts between HiLA aspects are possible and how to detect them. The practical applicability of HiLA is shown in a case study of a crisis management system

Model Transformations from Requirements to Web System Design

Requirements models are used to specify system functionalities from the customer viewpoint and are the starting point of software development. However, most Web engineering approaches do not provide a systematic method to build design models from requirements specification. We propose an approach using model transformations to close this gap. Our transformation rules are defined in the QVT language – a forthcoming OMG standard, which makes automatic model generation possible. This way design is kept consistent with the customer requirements.Deutsche Forschungsgemeinschaft (DFG) WI841/7-1EC 6th Framework project SENSORIA IST 01600

The distinct binding properties between avian/human influenza A virus NS1 and Postsynaptic density protein-95 (PSD-95), and inhibition of nitric oxide production

<p>Abstract</p> <p>Background</p> <p>The NS1 protein of influenza A virus is able to bind with many proteins that affect cellular signal transduction and protein synthesis in infected cells. The NS1 protein consists of approximately 230 amino acids and the last 4 amino acids of the NS1 C-terminal form a PDZ binding motif. Postsynaptic Density Protein-95 (PSD-95), which is mainly expressed in neurons, has 3 PDZ domains. We hypothesise that NS1 binds to PSD-95, and this binding is able to affect neuronal function.</p> <p>Result</p> <p>We conducted a yeast two-hybrid analysis, GST-pull down assays and co-immunoprecipitations to detect the interaction between NS1 and PSD-95. The results showed that NS1 of avian influenza virus H5N1 (A/chicken/Guangdong/1/2005) is able to bind to PSD-95, whereas NS1 of human influenza virus H1N1 (A/Shantou/169/2006) is unable to do so. The results also revealed that NS1 of H5N1 significantly reduces the production of nitric oxide (NO) in rat hippocampal neurons.</p> <p>Conclusion</p> <p>In summary, our study indicates that NS1 of influenza A virus can bind with neuronal PSD-95, and the avian H5N1 and human H1N1 influenza A viruses possess distinct binding properties.</p

Molla's music

Magister Artium - MAMolla's Music is a novella about Maureen (Molla), a white Afrikaans woman born in 1935 in Cape Town, who faced poverty and abandonment before apartheid and who, during apartheid, faced the choice between an unwanted pregnancy with a married man, and a carreer in music funded by the father who had betrayed her. Maureen is introduced in three sections with very different voices in each. In the first section she is depicted in the context of being cared for by a single mother with severe post natal depression. The short chapters and long sentences reflect the naïvity of the subject, whose unfiltered observations allow the reader to bear witness to the traumas that dictate her character later in life. She was so ashamed of her poverty, her father's abandonment, and her pregnancy, that she hid all memories of her past from her children and grandchildren and almost managed to die with all her secrets in tact. The second section becomes more sophisticated with longer chapters. The reader is guided through the fifties by a young adult whose adolescent memories inform the events that unfold over a mere two days. Finally, the last section consists of only one chapter, but it reviews an entire life. It is written in the first person, revealing the identity of the narrator. Maureen taught herself piano before school. Her father played the violin and her dedication to music seems to be a mechanism for connecting to him and what his absence from her life represents. It is an absense that eludes consolidation until her death. Molla proved to be such a gifted child that she skipped two years of school and took on music as an extra subject until matric, but financial strain and the shackles of patriarchy limited her options and only after years of working, does she apply to the UCT college of music. She inherits a piano from her landlords, who are evicted during the implementation of the Group Areas Act of 1957. In the years after that, playing piano becomes her private liberation practised in plain sight, on the only heirloom that persists from her past. When she dies, her granddaughter has a heritage that beckons to be resolved and remembered. She does not play the piano she inherited from her grandmother, but starts to investigate its past. In the course of Molla's Music, I explore themes of Afrikaner identity, and question modes of being for white Afrikaans women in South Africa today. By offering an intimate depiction of an individual's search for meaning, while negotiating the forces of Apartheid and patriarchy, especially as a confluence of forces, I hope to gain clarity with regard to my own questions about identity

Induction of cytopathic effect and cytokines in coxsackievirus B3-infected murine astrocytes

BACKGROUND: Coxsackievirus commonly infects children and occasionally causes severe meningitis and/or encephalitis in the newborn. The underlying mechanism(s) behind the central nervous system pathology is poorly defined. METHODS: It is hypothesized that astrocytes may be involved in inflammatory response induced by CVB3 infection. Here we discuss this hypothesis in the context of CVB3 infection and associated inflammatory response in primary mouse astrocytes. RESULTS: The results showed that coxsackievirus receptor (CAR) was distributed homogeneously on the astrocytes, and that CVB3 could infect and replicate in astrocytes, with release of infectious virus particles. CVB3 induced cytopathic effect and production of proinflammatory cytokines IL-1β, TNF-α, IL-6, and chemokine CXCL10 from astrocytes. CONCLUSION: These data suggest that direct astrocyte damage and cytokines induction could be a mechanism of virus-induced meningitis and/or encephalitis

Electronic properties of monolayer copper selenide with one-dimensional moir\'e patterns

Strain engineering is a vital way to manipulate the electronic properties of two-dimensional (2D) materials. As a typical representative of transition metal mono-chalcogenides (TMMs), a honeycomb CuSe monolayer features with one-dimensional (1D) moir\'e patterns owing to the uniaxial strain along one of three equivalent orientations of Cu(111) substrates. Here, by combining low-temperature scanning tunneling microscopy/spectroscopy (STM/S) experiments and density functional theory (DFT) calculations, we systematically investigate the electronic properties of the strained CuSe monolayer on the Cu(111) substrate. Our results show the semiconducting feature of CuSe monolayer with a band gap of 1.28 eV and the 1D periodical modulation of electronic properties by the 1D moir\'e patterns. Except for the uniaxially strained CuSe monolayer, we observed domain boundary and line defects in the CuSe monolayer, where the biaxial-strain and strain-free conditions can be investigated respectively. STS measurements for the three different strain regions show that the first peak in conduction band will move downward with the increasing strain. DFT calculations based on the three CuSe atomic models with different strain inside reproduced the peak movement. The present findings not only enrich the fundamental comprehension toward the influence of strain on electronic properties at 2D limit, but also offer the benchmark for the development of 2D semiconductor materials.Comment: 14 pages, 12 figures, 25 referenc

Deep Teaching: Materials for Teaching Machine and Deep Learning

[EN] Machine learning (ML) is considered to be hard because it is relatively complicated in comparison to other topics of computer science. The reason is that machine learning is based heavily on mathematics and abstract concepts. This results in an entry barrier for students: Most students want to avoid such difficult topics in elective courses or self-study. In the project Deep.Teaching we address these issues: We motivate by selected applications and support courses as well as self-study by giving practical exercises for different topics in machine learning. The teaching material, provided as jupyter notebooks, consists of theoretical and programming sections. For didactical reasons, we designed programming exercises such that the students have to deeply understand the concepts and principles before they can start to implement a solution. We provide all necessary boilerplate code such that the students can primarily focus on the educational objectives of the exercises. We used different ways to give feedback for self-study: obscured solutions for mathematical results, software tests with assert statements, and graphical illustrations of sample solutions. All of the material is published under a permissive license. Developing jupyter notebooks collaboratively for educational purposes poses some problems. We address these issues and provide solutions/best practices.The project Deep.Teaching is funded by the German National Ministry of Education and Research (BMBF), project number 01IS17056.Herta, C.; Voigt, B.; Baumann, P.; Strohmenger, K.; Jansen, C.; Fischer, O.; Zhang, G.... (2019). Deep Teaching: Materials for Teaching Machine and Deep Learning. En HEAD'19. 5th International Conference on Higher Education Advances. Editorial Universitat Politècnica de València. 1153-1131. https://doi.org/10.4995/HEAD19.2019.9177OCS1153113