Structure−Activity Relationships of Cinnamate Ester Analogues as Potent Antiprotozoal Agents

Protozoal infections are still a global health problem, threatening the lives of millions of people around the world, mainly in impoverished tropical and sub-tropical regions. Thus, in view of the lack of efficient therapies and increasing resistances against existing drugs, this study describes the antiprotozoal potential of synthetic cinnamate ester analogues and their structure-activity relationships. In general, Leishmania donovani and Trypanosoma brucei were quite susceptible to the compounds in a structure-dependent manner. Detailed analysis revealed a key role of the substitution pattern on the aromatic ring and a marked effect of the side chain on the activity against these two parasites. The high antileishmanial potency and remarkable selectivity of the nitro-aromatic derivatives suggested them as promising candidates for further studies. On the other hand, the high in vitro potency of catechol-type compounds against T. brucei could not be extrapolated to an in vivo mouse model.     

Semi‐Markovian modelling and performance analysis of variable rate traffic in ATM networks

Semi‐Markovian processes (SMP) serve as a versatile means to model various traffic types generated by sources or superposed from links in ATM networks. An efficient discrete time analysis method is proposed for SMP/G/1 queueing systems to evaluate ATM switches with non‐renewal input. Some basic results are derived for the autocorrelation function of semi‐Markovian processes and for the effect of state space reduction on autocorrelation, which show how to represent correlated traffic with given characteristic by an adequate SMP model of limited size. This revised version was published online in June 2006 with corrections to the Cover Date.     

Finite constants: characterizations of a new decidable set of constants

Constant propagation, the replacement of program terms which represent a unique value at run time by their values, is a classical program optimization method. In spite of being treated for years, constant propagation still has been in the unsatisfactory phase of heuristics. We enhance the known constant propagation techniques to obtain an algorithm which is optimal for programs without loops. Fundamental is the introduction of a new decidable set of constants, the finite constants. This set has two different characterizations: a denotational one, which directly specifies our iterative algorithm and an operational one, which delivers the completeness or optimality of this algorithm for programs without loops. The algorithm is implemented in a commercial compiler project.     

Modellqualität als Indikator für Softwarequalität: eine Taxonomie

Zusammenfassung  Komplexit?t, Anforderungsmanagement und Variantenvielfalt sind zentrale Herausforderungen bei der Entwicklung und Evolution heutiger softwaregesteuerter Systeme. Diesen wird zunehmend durch den Einsatz modellbasierter Entwicklungsmethoden begegnet. Dadurch wird das Modell zum zentralen Artefakt und die Erstellung und Nutzung von Modellen zu einer zentralen T?tigkeit in der Softwareentwicklung. Mit der Bedeutung der Modelle steigen auch die Ansprüche an ihre Qualit?t. Dieser Beitrag untersucht die Implikationen, die daraus entstehen, insbesondere werden sinnvolle Qualit?tsmerkmale für softwarebeschreibende Modelle identifiziert und diskutiert.     

What do we learn from binding features? Evidence for multilevel feature integration.

Four experiments were conducted to investigate the relationship between the binding of visual features (as measured by their aftereffects on subsequent binding) and the learning of feature-conjunction probabilities. Both binding and learning effects were obtained, but they did not interact. Interestingly, (shape-color) binding effects disappeared with increasing practice, presumably because of the fact that only 1 of the features involved was relevant to the task. However, this instability was only observed for arbitrary, not highly overlearned combinations of simple geometric features and not for real objects (colored pictures of a banana and strawberry), where binding effects were strong and resistant to practice. These findings suggest that learning has no direct impact on the strength or resistance of bindings or on speed with which features are bound; however, learning does affect the amount of attention particular feature dimensions attract, which again can influence which features are considered in binding. (PsycINFO Database Record (c) 2011 APA, all rights reserved)