Extended-Linking Services: towards a Quality Web

A URL takes requesters from a citation to a destination… provided, of course, the URL is still valid. The current chaotic web is wonderful in its way. However, within this chaotic web, we believe there is a need for a high-quality web of vetted information. The emerging OpenURL standard is the cornerstone of a worldwide web with high-quality links that feature properties such as: •Persistence: Increase the probable lifetime of citations. •Multiplicity: Produce a menu of targeted services for each citation. •Context-Sensitivity: Resolve a citation in a manner appropriate to the user and to the context. To encourage the development of extended-linking services, NISO formed a committee to develop a standard OpenURL syntax. Our immediate goal is to serve the scholarly-information community immediately. However, the OpenURL technique is widely applicable, and we expect to serve many other information communities

Dosing Optimization of Beta-Lactam Antibiotics using Parametric and Nonparametric Population Pharmacokinetic Models

This thesis is mainly focused on dosing evaluation of old antibiotics using parametric and nonparametric population pharmacokinetic models. Additionally, modelling-related challenges during dosing evaluation were identified and recommendations on the use of these models during drug development and in clinical practise were set up

The state of MIIND

MIIND (Multiple Interacting Instantiations of Neural Dynamics) is a highly modular multi-level C++ framework, that aims to shorten the development time for models in Cognitive Neuroscience (CNS). It offers reusable code modules (libraries of classes and functions) aimed at solving problems that occur repeatedly in modelling, but tries not to impose a specific modelling philosophy or methodology. At the lowest level, it offers support for the implementation of sparse networks. For example, the library SparseImplementationLib supports sparse random networks and the library LayerMappingLib can be used for sparse regular networks of filter-like operators. The library DynamicLib, which builds on top of the library SparseImplementationLib, offers a generic framework for simulating network processes. Presently, several specific network process implementations are provided in MIIND: the Wilson–Cowan and Ornstein–Uhlenbeck type, and population density techniques for leaky-integrate-and-fire neurons driven by Poisson input. A design principle of MIIND is to support detailing: the refinement of an originally simple model into a form where more biological detail is included. Another design principle is extensibility: the reuse of an existing model in a larger, more extended one. One of the main uses of MIIND so far has been the instantiation of neural models of visual attention. Recently, we have added a library for implementing biologically-inspired models of artificial vision, such as HMAX and recent successors. In the long run we hope to be able to apply suitably adapted neuronal mechanisms of attention to these artificial models

Moroccorp: tien miljoen woorden uit twee Marokkaans- Nederlandse chatkanalen

In dit artikel stellen we een nieuw corpus voor van computer-gemedieerde communicatie in het Nederlands door Marokkaans-Nederlandse taalgebruikers, dat bestaat uit tien miljoen woorden chat-materiaal. We behandelen de achtergrond, de compilatiemethode en de interne structuur van het corpus, en we leggen het verband tussen ons eigen werk en eerdere pogingen om een corpus van Nederlandse chattaal te bouwen. We hebben ook een Stable Lexical Marker analyse uitgevoerd en een gevalstudie over een welbekende morfosyntactische eigenschap van het Marokkaans Nederlands om op die manier de representativiteit van het corpus te beoordelen.Trefwoorden: Nederlands, marokkaans nederlands, corpus, chat, stable lexical marker analysis, etnisch nederlands, representativitei

Combinatorial structures and processing in Neural Blackboard Architectures

We discuss and illustrate Neural Blackboard Architectures (NBAs) as the basis for variable binding and combinatorial processing the brain. We focus on the NBA for sentence structure. NBAs are based on the notion that conceptual representations are in situ, hence cannot be copied or transported. Novel combinatorial struc- tures can be formed with these representations by embedding them in NBAs. We discuss and illustrate the main characteristics of this form of combinatorial pro- cessing. We also illustrate the NBA for sentence structures by simulating neural activity as found in recently reported intracranial brain observations. Furthermore, we will show how the NBA can account for ambiguity resolution and garden path effects in sentence processing

The necessity of connection structures in neural models of variable binding

In his review of neural binding problems, Feldman (Cogn Neurodyn 7:1-11, 2013) addressed two types of models as solutions of (novel) variable binding. The one type uses labels such as phase synchrony of activation. The other (‘connectivity based') type uses dedicated connections structures to achieve novel variable binding. Feldman argued that label (synchrony) based models are the only possible candidates to handle novel variable binding, whereas connectivity based models lack the flexibility required for that. We argue and illustrate that Feldman's analysis is incorrect. Contrary to his conclusion, connectivity based models are the only viable candidates for models of novel variable binding because they are the only type of models that can produce behavior. We will show that the label (synchrony) based models analyzed by Feldman are in fact examples of connectivity based models. Feldman's analysis that novel variable binding can be achieved without existing connection structures seems to result from analyzing the binding problem in a wrong frame of reference, in particular in an outside instead of the required inside frame of reference. Connectivity based models can be models of novel variable binding when they possess a connection structure that resembles a small-world network, as found in the brain. We will illustrate binding with this type of model with episode binding and the binding of words, including novel words, in sentence structures