Attractive periodic sets in discrete-time recurrent networks (with emphasis on fixed-point stability and bifurcations in two-neuron networks)

We perform a detailed fixed-point analysis of two-unit recurrent neural networks with sigmoid-shaped transfer functions. Using geometrical arguments in the space of transfer function derivatives, we partition the network state-space into distinct regions corresponding to stability types of the fixed points. Unlike in the previous studies, we do not assume any special form of connectivity pattern between the neurons, and all free parameters are allowed to vary. We also prove that when both neurons have excitatory self-connections and the mutual interaction pattern is the same (i.e., the neurons mutually inhibit or excite themselves), new attractive fixed points are created through the saddle-node bifurcation. Finally, for an N-neuron recurrent network, we give lower bounds on the rate of convergence of attractive periodic points toward the saturation values of neuron activations, as the absolute values of connection weights grow.     

Joining High Thickness Materials by Sewing – first Modelling Steps of the Stitched Place

Applied Composite Materials - Many textile products are using materials with higher thickness like foams, spacer fabrics and nonwoven materials in order to provide comfortable softness of the...     

Multiple functionalization of fluorescent nanoparticles for specific biolabeling and drug delivery of dopamine

The development of fluorescent biolabels for specific targeting and controlled drug release is of paramount importance in biological applications due to their potential in the generation of novel tools for simultaneous diagnosis and treatment of diseases. Dopamine is a neurotransmitter involved in several neurological diseases, such as Parkinson's disease and attention deficit hyperactivity disorder (ADHD), and the controlled delivery of its agonists already proved to have beneficial effects both in vitro and in vivo. Here, we report the synthesis and multiple functionalization of highly fluorescent CdSe/CdS quantum rods for specific biolabeling and controlled drug release. After being transferred into aqueous media, the nanocrystals were made highly biocompatible through PEG conjugation and covered by a carbohydrate shell, which allowed specific GLUT-1 recognition. Controlled attachment of dopamine through an ester bond also allowed hydrolysis by esterases, yielding a smart nanotool for specific biolabeling and controlled drug release.     

Behaviourally relevant road categorisation: a step towards self-explaining rural roads

In contrast to motorways, rural roads are characterised by a large variation in design, appearance and function which is reflected in a comparatively large number of rural road categories. Depending on these categories, a certain (normative) behaviour is usually expected from the driver. These normative behavioural expectations are conveyed to the driver either by formal cues (e.g. speed limit signs) or are expected to be inferred from the road appearance or the affordance (Gibson, J.J., 1986. The Ecological Approach to Visual Perception. Lawrence Erlbaum, Hillsdale (New Jersey)) of the respective road situation. Unsafe situations are likely to occur if the perceived message conveyed by cues or affordances does not match the normative behavioural expectations of the official road category. In order to avoid such mismatch it is important to know how drivers categorise (rural) roads and which elements are used for this subjective and behaviourally relevant road categorisation. We therefore summarized the processes behind this categorisation in a model and conducted a study in a laboratory setting during which subjects were asked to rate a variety of rural road pictures. The study revealed that drivers distinguish between three different rural road categories which can be distinguished with comparatively few objective criteria. Applying these criteria helps to categorise and design rural roads along self-explaining road principles.     

Discovery and structure-activity relationship studies of a unique class of HIV-1 integrase inhibitors

HIV-1 integrase (IN) is an essential enzyme for viral replication and a validated target for the development of drugs against AIDS. Currently there are no approved drugs that target IN. However, new IN inhibitors are under clinical investigation. As more IN inhibitors enter human drug trials, there is a growing need for the design of novel lead compounds with diverse structural scaffolds and promising pharmacokinetic properties to counteract the difficulties observed with first-generation IN inhibitors. We have identified a novel class of IN inhibitors through the systematic exploration of structure-activity relationships in a series of linomide analogues. The predicted bound conformation of the most active analogues inside the IN active site also supports the observed structure-activity correlation in this new compound class.