The impact of the Hebbian learning rule on research in behavioural neuroscience.

Hebb's principal theoretical propositions, the cell assembly and the nature of synaptic change, were generated at a time when the focus of work in behavioural neuroscience was directed at understanding issues such as the principles governing the behaviour of animals in neuropsychological studies of learning and memory and the role of drives in the control of behaviours like sex and feeding and drinking. It was not until attention shifted to understanding the neural underpinnings of learning and memory that Hebb's propositions had an impact on behavioural neuroscience as they provided a simple, and testable, mechanism for synaptic plasticity observed both in learning and in other forms of experience-dependent neural change. But much of the field remains interested in other issues such as sensation and perception, motivation, attention, and so on, and to date, Hebb's propositions have had little impact. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Development and implementation of a NURBS curve motion interpolator

This paper deals with the issues of development and implementation of a real-time NURBS interpolator for a six-axis robot. Using an open-architecture controller system as a testbed, a real-time NURBS curve interpolator was developed, implemented and tested. Sample runs were conducted with the resulting trajectories measured in real-time during robot motion. The resulting trajectories are analyzed, discussed and compared with those from a commonly used point-to-point approximation technique. The real-time NURBS curve interpolator's feasibility, advantages and related issues are also discussed.     

Influence of segregation in quantum well structures

The potential associated with quantum well (QW) structures is usually assumed to be a step function; this implies a compositional abruptness at each interface. But abrupt interfaces do not occur in practice, especially if one of the atoms segregates during growth. This leads to asymmetries in the QW potentials which could radically affect device performance.     

Designing collaborative,constructionist and contextual applications for handheld devices

This paper explores current applications for handheld devices and questions which of these make full use of the unique attributes of handheld devices in order to facilitate learning in a pedagogically sensible manner. In order to do so, the paper presents a functional framework which analyses handheld application in relation to their use as well as the pedagogical underpinning, if any, that informs their development. Our framework currently consists of seven distinct categories of application, which we term: administrative, referential, interactive, microworld, data collection, location aware and collaborative. We argue that three categories, namely data collection, location aware and collaborative, are particularly suited to learning with handheld devices when they are informed by collaborative, contextual and constructionist learning theories. Furthermore, we contend that applications of the type just outlined deserve further research since they are not attempting to replicate, or even augment, existing learning scenarios but rather they try to create new learning opportunities which would not be possible without (mobile) technology. Finally, the authors introduce a number of applications and learning scenarios that they have developed for handheld devices and explain their position within the framework.     

Wood processing variables and adhesive joint performance

In order to obtain a bonded wood product from the tree, wood must be subjected to a series of processes. These include, among others, vital processes like drying of the green wood and machining of the surfaces of the dried wood in preparation for bonding. However, when wood is machined with dull blades, thermal degradation of the wood frequently occurs. The effects of kiln drying and thermal degradation of wood on the performance of the adhesive joints subsequently formed from such wood were investigated. Tapered double cantilever beam (TDCB) test specimens obtained from hard maple and phenol–resorcinol–formaldehyde (PRF) adhesives were used in the investigations. The enhancement of fracture energy due to the reduction in the moisture content of wood, the improved performance of adhesive joints due to rejointing of wood surfaces before bonding, and the reduction of adhesive joint strength resulting from thermal degradation of wood are presented and discussed.     

Single amino acid substitutions can further increase the stability of a thermophilic L-lactate dehydrogenase

Lactate dehydrogenases are of considerable interest as stereospecificcatalysts in the chemical preparation of enantiomerically pure-hydroxyacid synthons. For such applications in synthetic organicchemistry it would be desirable to have enzymes which tolerateelevated temperatures for prolonged reaction times, to increaseproductivity and to extend then applicability to poor substrates.Here, two examples are reported of significant thermostabilizations,induced by sitedirected mutagenesis, of an already thermostableprotein, the L-lactate dehydrogenase (EC 1.1.1.27 [EC] , 35 kDa permonomer subunit) from Bacillus stearothermophilus. Thermal inactivationof this enzyme is accompanied by irreversible unfolding of thenative protein structure. The replacement of Argl71 by Tyr stabilizesthe enzyme against thermal inactivation and unfolding. Thisstabilizing effect appears to be based on improved interactionsbetween the subunits in the core of the active dimeric or tetramericforms of the enzyme. The thermal stability of L-lactate dehydrogenasevariants with an active site Arg residue, either in the 171(wild-type) or in the 102 position, is further increased bysulfate ions. The two stabilizing effects are additive, as foundfor the Argl71Tyr/ Gln1O2Arg double mutant, for which the stabilityof the protein in 100 mM sulfate solution reaches that of L-lactatedehydrogenases from extreme thermophiles. All mutant proteinsretain significant catalytic activity, both in the presenceand absence of stnhilfoing salts, and are viable catalysts inpreparative scale reactions.     

Clustering semantically heterogeneous distributed aggregate databases

Databases developed independently in a common open distributed environment may be heterogeneous with respect to both data schema and the embedded semantics. Managing schema and semantic heterogeneities brings considerable challenges to learning from distributed data and to support applications involving cooperation between different organisations. In this paper, we are concerned mainly with heterogeneous databases that hold aggregates on a set of attributes, which are often the result of materialised views of native large-scale distributed databases. A model-based clustering algorithm is proposed to construct a mixture model where each component corresponds to a cluster which is used to capture the contextual heterogeneity among databases from different populations. Schema heterogeneity, which can be recast as incomplete information, is handled within the clustering process using Expectation-Maximisation estimation and integration is carried out within a clustering iteration. Our proposed algorithm resolves the schema heterogeneity as part of the clustering process, thus avoiding transformation of the data into a unified schema. Results of algorithm evaluation on classification, scalability and reliability, using both real and synthetic data, demonstrate that our algorithm can achieve good performance by incorporating all of the information from available heterogeneous data. Our clustering approach has great potential for scalable knowledge discovery from semantically heterogeneous databases and for applications in an open distributed environment, such as the Semantic Web.     

A New Approach to Two-View Motion Segmentation Using Global Dimension Minimization

We present a new approach to rigid-body motion segmentation from two views. We use a previously developed nonlinear embedding of two-view point correspondences into a 9-dimensional space and identify the different motions by segmenting lower-dimensional subspaces. In order to overcome nonuniform distributions along the subspaces, whose dimensions are unknown, we suggest the novel concept of global dimension and its minimization for clustering subspaces with some theoretical motivation. We propose a fast projected gradient algorithm for minimizing global dimension and thus segmenting motions from 2-views. We develop an outlier detection framework around the proposed method, and we present state-of-the-art results on outlier-free and outlier-corrupted two-view data for segmenting motion.     

Moisture absorption into ultrathin hydrophilic polymer films on different substrate surfaces

Moisture absorption into ultrathin poly(vinyl pyrrolidone) (PVP) films with varying thickness was examined using X-ray reflectivity (XR) and quartz crystal microbalance (QCM) measurements. Two different surfaces were used for the substrate: a hydrophilic silicon oxide (SiO_x) and a hydrophobic hexamethyldisilazane (HMDS) treated silicon oxide surface. The total equilibrium moisture absorption (solubility) was insensitive to the surface treatment in the thickest films (≈150 nm). However, strong reductions in the equilibrium uptake with decreasing PVP film thickness were observed on the HMDS surfaces, while the SiO_x surface exhibited thickness independent equilibrium absorption. The decreased absorption with decreasing film thickness is attributed a depletion layer of water near the polymer/HMDS interface, arising from hydrophobic interactions between the surface and water. The diffusivity of water decreased when the film thickness was less than 60 nm, independent of the surface treatment. Changes in the properties of ultrathin polymer films occur even in plasticized films containing nearly 50% water.