Functional assessment tools for paediatric clients with Juvenile Chronic Arthritis: An update and review for occupational therapists

Juvenile chronic arthritis (JCA) is one cause of chronic illness and disability in childhood. Traditional clinical assessment of clients with JCA include objective measures of joint deformity, joint swelling, range of motion, duration of morning stiffness, pain, walking speed, running speed and muscle strength. In many instances, these traditional measures have little or no significance or relevance to paediatric clients and their parents whereas functional skills used in everyday living are more likely to be meaningful. Measures of physical, social, and psychological functioning ensure a comprehensive health assessment. Responsible occupational therapy assessment and management of paediatric clients diagnosed with JCA requires the use of reliable, valid and sensitive measures of function. Several instruments are now available which measure a child's or adolescent's functional abilities. In this paper, JCA and the impact of JCA on functional development are reviewed. As well, seven functional assessment tools designed for use with paediatric clients with JCA which occupational therapists can use in their clinical practice will be appraised. The various characteristics of these tools are discussed in order to assist practitioners and researchers in selecting the functional instrument which best meets their needs.

Microstrip circular phased array design and development using microwave antenna CAD tools

The complex design and development of a planar multilayer phased array antenna in microstrip technology can be simplified using two commercially available design tools 1) Ansoft Ensemble and 2) HP-EEsof Touchstone. In the approach presented here, Touchstone is used to design RF switches and phase shifters whose scattering parameters are incorporated in Ensemble simulations using its black box tool. Using this approach, Ensemble is able to fully analyze the performance of radiating and beamforming layers of a phased array prior to its manufacturing. This strategy is demonstrated in a design example of a 12-element linearly-polarized circular phased array operating at L band. A comparison between theoretical and experimental results of the array is demonstrated.

Branching processes and computational collapse of discretized unimodal mappings

In computer simulations of smooth dynamical systems, the original phase space is replaced by machine arithmetic, which is a finite set. The resulting spatially discretized dynamical systems do not inherit all functional properties of the original systems, such as surjectivity and existence of absolutely continuous invariant measures. This can lead to computational collapse to fixed points or short cycles. The paper studies loss of such properties in spatial discretizations of dynamical systems induced by unimodal mappings of the unit interval. The problem reduces to studying set-valued negative semitrajectories of the discretized system. As the grid is refined, the asymptotic behavior of the cardinality structure of the semitrajectories follows probabilistic laws corresponding to a branching process. The transition probabilities of this process are explicitly calculated. These results are illustrated by the example of the discretized logistic mapping.

Computational differentiation of N-terminal signal peptides and transmembrane helices

Signal peptides and transmembrane helices both contain a stretch of hydrophobic amino acids. This common feature makes it difficult for signal peptide and transmembrane helix predictors to correctly assign identity to stretches of hydrophobic residues near the N-terminal methionine of a protein sequence. The inability to reliably distinguish between N-terminal transmembrane helix and signal peptide is an error with serious consequences for the prediction of protein secretory status or transmembrane topology. In this study, we report a new method for differentiating protein N-terminal signal peptides and transmembrane helices. Based on the sequence features extracted from hydrophobic regions (amino acid frequency, hydrophobicity, and the start position), we set up discriminant functions and examined them on non-redundant datasets with jackknife tests. This method can incorporate other signal peptide prediction methods and achieve higher prediction accuracy. For Gram-negative bacterial proteins, 95.7% of N-terminal signal peptides and transmembrane helices can be correctly predicted (coefficient 0.90). Given a sensitivity of 90%, transmembrane helices can be identified from signal peptides with a precision of 99% (coefficient 0.92). For eukaryotic proteins, 94.2% of N-terminal signal peptides and transmembrane helices can be correctly predicted with coefficient 0.83. Given a sensitivity of 90%, transmembrane helices can be identified from signal peptides with a precision of 87% (coefficient 0.85). The method can be used to complement current transmembrane protein prediction and signal peptide prediction methods to improve their prediction accuracies. (C) 2003 Elsevier Inc. All rights reserved.