Speed‐up and performance evaluation of piecewise‐linear DC analysis

The good convergence properties of piecewise‐linear (PWL) DC analysis have been thoroughly discussed in many papers. This paper, in turn, concentrates on the speed of PWL DC analysis, where the boundary crossing of linear regions plays a crucial role. Fast methods are presented for performing the following boundary‐crossing computations: LU‐decomposition update, matrix‐equation solution, boundary‐crossing direction, and damping‐factor determination. Special attention is given to those PWL DC analysis methods that perform PWL modelling of the non‐linear components on the fly; an adaptive method is proposed for controlling the accuracy of PWL modelling and speeding up simulation. The computational efficiency of the accelerated PWL DC analysis is discussed and compared with that of conventional, Newton–Raphson iteration‐based, DC analysis. Finally, the performance evaluation is completed with realistic simulation examples: it is demonstrated that the speed of the accelerated PWL DC analysis is comparable with that of the conventional DC analysis. Copyright © 2006 John Wiley & Sons, Ltd.     

Tectonics and architectonic quality in recently published Finnish log architecture: Corresponding architects’ perceptions

Due to the global increase in wood construction, it is crucial for architects to understand wood. In Finland, log building, a special subset of industrially manufactured massive timber construction materials is experiencing a renaissance. Cultural aspects combined with newer technical developments make log a complex material from the viewpoint of architectonic expression. To inform practicing architects, the aim of this study is to explore how the tectonics of logs contribute to the architectonic quality of log architecture. Semi-structured interviews among architects of twelve recently published log buildings are conducted. The results describe how architectonic quality is perceived among participants, and features of logs related to tectonics that they consider to be of importance in terms of architectonic quality. These features include the statics of log construction and log's nature as a simultaneously insulating, load-bearing and visual material. Differences between industrial and hand-hewn logs, as well as other architectural aspects of using logs in contemporary architecture are discussed. Especially the “non-settling” log was perceived to have manifold implications for the architectonic possibilities of log architecture. The results are of practical importance to designing architects and the log industry. Theoretical implications include tangible information on architectonic quality and tectonics of log building.     

Principle of Learning Metrics for Exploratory Data Analysis

Visualization and clustering of multivariate data are usually based on mutual distances of samples, measured by heuristic means such as the Euclidean distance of vectors of extracted features. Our recently developed methods remove this arbitrariness by learning to measure important differences. The effect is equivalent to changing the metric of the data space. It is assumed that variation of the data is important only to the extent it causes variation in auxiliary data which is available paired to the primary data. The learning of the metric is supervised by the auxiliary data, whereas the data analysis in the new metric is unsupervised. We review two approaches: a clustering algorithm and another that is based on an explicitly generated metric. Applications have so far been in exploratory analysis of texts, gene function, and bankruptcy. Relationships of the two approaches are derived, which leads to new promising approaches to the clustering problem.     

Photoswitchable Superabsorbency Based on Nanocellulose Aerogels

Chemical vapor deposition of a thin titanium dioxide (TiO₂) film on lightweight native nanocellulose aerogels offers a novel type of functional material that shows photoswitching between water‐superabsorbent and water‐repellent states. Cellulose nanofibrils (diameters in the range of 5–20 nm) with native crystalline internal structures are topical due to their attractive mechanical properties, and they have become relevant for applications due to the recent progress in the methods of their preparation. Highly porous, nanocellulose aerogels are here first formed by freeze‐drying from the corresponding aqueous gels. Well‐defined, nearly conformal TiO₂ coatings with thicknesses of about 7 nm are prepared by chemical vapor deposition on the aerogel skeleton. Weighing shows that such TiO₂‐coated aerogel specimens essentially do not absorb water upon immersion, which is also evidenced by a high contact angle for water of 140° on the surface. Upon UV illumination, they absorb water 16 times their own weight and show a vanishing contact angle on the surface, allowing them to be denoted as superabsorbents. Recovery of the original absorption and wetting properties occurs upon storage in the dark. That the cellulose nanofibrils spontaneously aggregate into porous sheets of different length scales during freeze‐drying is relevant: in the water‐repellent state they may stabilize air pockets, as evidenced by a high contact angle, in the superabsorbent state they facilitate rapid water‐spreading into the aerogel cavities by capillary effects. The TiO₂‐coated nanocellulose aerogels also show photo‐oxidative decomposition, i.e., photocatalytic activity, which, in combination with the porous structure, is interesting for applications such as water purification. It is expected that the present dynamic, externally controlled, organic/inorganic aerogels will open technically relevant approaches for various applications.     

Clustering based on conditional distributions in an auxiliary space.

We study the problem of learning groups or categories that are local in the continuous primary space but homogeneous by the distributions of an associated auxiliary random variable over a discrete auxiliary space. Assuming that variation in the auxiliary space is meaningful, categories will emphasize similarly meaningful aspects of the primary space. From a data set consisting of pairs of primary and auxiliary items, the categories are learned by minimizing a Kullback-Leibler divergence-based distortion between (implicitly estimated) distributions of the auxiliary data, conditioned on the primary data. Still, the categories are defined in terms of the primary space. An online algorithm resembling the traditional Hebb-type competitive learning is introduced for learning the categories. Minimizing the distortion criterion turns out to be equivalent to maximizing the mutual information between the categories and the auxiliary data. In addition, connections to density estimation and to the distributional clustering paradigm are outlined. The method is demonstrated by clustering yeast gene expression data from DNA chips, with biological knowledge about the functional classes of the genes as the auxiliary data.     

Oral findings in patients with active or inactive Crohn''s disease

The frequency and type of oral mucosal lesions, dental infections, and salivary constituents were evaluated in 53 patients with Crohn's disease, who were divided into inactive, mildly active, and severely active groups on the basis of clinical and endoscopic criteria. Buccal biopsies from nine patients with active disease showed morphologic changes that suggested Crohn's disease-related lesions. Panoramic radiographs revealed more infectious foci in the teeth of patients with active Crohn's disease than in patients with inactive disease. Salivary flow rate, buffering capacity, total protein, amylase, and IgA and IgG concentrations did not differ with respect to the activity of Crohn's disease. The observed mucosal inflammation in patients with active Crohn's disease, although high in frequency, was mild and did not need therapy, but the great number of dental infections in association with the activity of Crohn's disease should be taken into account in the treatment of these patients.     

Effect of source near- and far-field variations on the accuracy of multimode fibre attenuation measurements

The error incurred in fibre attenuation measurements due to variations in the launch near- and far-fields is examined for a statistically uniform near field and a cosp ? far field. It is found that even under well controlled conditions, spatial and wavelength variations could easily lead to interlaboratory errors in excess of ± 0.03 dB.     

Technique for reducing spatial and wavelength variations of launch spot in fibre attenuation measurements

A launching technique based on the use of a large step-index rod with a ground end face is described. Experimental results indicate a significant reduction in spatial and wavelength variations. Based on theoretical considerations, the resultant attenuation error in interlaboratory experiments is estimated to be about ± 0.03 dB.