Behaviour state analysis in Rett syndrome: Continuous data reliability measurement

Awareness of optimal behaviour states of children with profound intellectual disability has been reported in the literature as a potentially useful tool for planning intervention within this population. Some arguments have been raised, however, which question the reliability and validity of previously published work on behaviour state analysis. This article sheds light on the debate by presenting two stages of a study of behaviour state analysis for eight girls with Rett syndrome. The results support Mudford, Hogg, and Roberts' (1997, 1999) concerns with the pooling of participant data. The results of Stage 2 also suggest, however, that most categories of behaviour state can be reliably distinguished once definitions of behaviours for each state are clearly defined.

Mutational analysis of the large periplasmic loop 7-8 of the putrescine transporter PotE in Escherichia coli

The PotE protein is a putrescine-ornithine antiporter found in many gram-negative bacteria. It is a member of the APA family of transporters and has 12 predicted alpha-helical transmembrane spanning segments (TMS). While the substrate binding site has previously been mapped to a region near the surface of the cytoplasmic lipid layer, no structural feature within the periplasmic domains of PotE have been shown to be important for function. We examined the role of the only large outer loop, situated between transmembrane spanning segment 7 and 8, in putrescine uptake. Deletion of the highly conserved amino acids in the region closest to transmembrane spanning segment 7 produced a protein with little activity. Glycine-scanning mutagenesis of this region showed that Val(249) and Leu(254) were required for optimal transporter function. The V249G mutant transported putrescine at a lower maximal rate compared to wild-type (WT) but with the same substrate binding affinity. In contrast, the L254G mutant had a higher substrate affinity. A series of Val(249) mutants indicated that the hydrophobicity of this residue, which is located at or near the membrane surface, is important for PotE function. Secondary structure predictions of the large outer loop indicated the presence of a hydrophobic alpha-helix in the centre with a hydrophobic region at each end suggesting that the loop was not entirely exposed to the aqueous periplasmic space. The study shows that loop 7-8 is important for PotE function, possibly by forming a re-entrant loop in the channel of the transporter. (C) 2003 Elsevier Ltd. All rights reserved.

Optimal sampling strategy for estimation of spatial genetic structure in tree populations

Fine-scale spatial genetic structure (SGS) in natural tree populations is largely a result of restricted pollen and seed dispersal. Understanding the link between limitations to dispersal in gene vectors and SGS is of key interest to biologists and the availability of highly variable molecular markers has facilitated fine-scale analysis of populations. However, estimation of SGS may depend strongly on the type of genetic marker and sampling strategy (of both loci and individuals). To explore sampling limits, we created a model population with simulated distributions of dominant and codominant alleles, resulting from natural regeneration with restricted gene flow. SGS estimates from subsamples (simulating collection and analysis with amplified fragment length polymorphism (AFLP) and microsatellite markers) were correlated with the 'real' estimate (from the full model population). For both marker types, sampling ranges were evident, with lower limits below which estimation was poorly correlated and upper limits above which sampling became inefficient. Lower limits (correlation of 0.9) were 100 individuals, 10 loci for microsatellites and 150 individuals, 100 loci for AFLPs. Upper limits were 200 individuals, five loci for microsatellites and 200 individuals, 100 loci for AFLPs. The limits indicated by simulation were compared with data sets from real species. Instances where sampling effort had been either insufficient or inefficient were identified. The model results should form practical boundaries for studies aiming to detect SGS. However, greater sample sizes will be required in cases where SGS is weaker than for our simulated population, for example, in species with effective pollen/seed dispersal mechanisms.

Genetic and economic analysis of a targeted marker-assisted wheat breeding strategy

The advent of molecular markers as a tool to aid selection has provided plant breeders with the opportunity to rapidly deliver superior genetic solutions to problems in agricultural production systems. However, a major constraint to the implementation of marker-assisted selection (MAS) in pragmatic breeding programs in the past has been the perceived high relative cost of MAS compared to conventional phenotypic selection. In this paper, computer simulation was used to design a genetically effective and economically efficient marker-assisted breeding strategy aimed at a specific outcome. Under investigation was a strategy involving the integration of both restricted backcrossing and doubled haploid (DH) technology. The point at which molecular markers are applied in a selection strategy can be critical to the effectiveness and cost efficiency of that strategy. The application of molecular markers was considered at three phases in the strategy: allele enrichment in the BC1F1 population, gene selection at the haploid stage and the selection for recurrent parent background of DHs prior to field testing. Overall, incorporating MAS at all three stages was the most effective, in terms of delivering a high frequency of desired outcomes and at combining the selected favourable rust resistance, end use quality and grain yield alleles. However, when costs were included in the model the combination of MAS at the BC1F1 and haploid stage was identified as the optimal strategy. A detailed economic analysis showed that incorporation of marker selection at these two stages not only increased genetic gain over the phenotypic alternative but actually reduced the over all cost by 40%.

Edge-to-edge matching and its applications - Part I. Application to the simple HCP/BCC system

The edge-to-edge matching crystallographic model has been used to predict all the orientation relationships (OR) between crystals that have simple hexagonal close packed (HCP) and body-centered cubic (BCC) structures. Using the critical values for the interatomic spacing misfit along the matching directions and the cl-value mismatch between matching planes, the model predicted all the four common ORs, namely the Burgers OR, the Potter OR, the Pitsch-Schrader OR and the Rong Dunlop OR, together with the corresponding habit planes. Taking the c(H)/a(H) and a(H)/a(B) ratios as variables, where H and B denote the HCP and BCC structures respectively, the model also predicted the relationship between these variables and the four ORs. These predictions are perfectly consistent with the published experimental results. As was the case in the FCC/BCC system, the edge-to-edge matching model has been shown to be a powerful tool for predicting the crystallographic features of diffusion-controlled phase transformations. (C) 2004 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Optimal Paths and Costs of Adjustment in Dynamic DEA Models: With Application to Chilean Department Stores

In this paper we propose a range of dynamic data envelopment analysis (DEA) models which allow information on costs of adjustment to be incorporated into the DEA framework. We first specify a basic dynamic DEA model predicated on a number or simplifying assumptions. We then outline a number of extensions to this model to accommodate asymmetric adjustment costs, non-static output quantities, non-static input prices, and non-static costs of adjustment, technological change, quasi-fixed inputs and investment budget constraints. The new dynamic DEA models provide valuable extra information relative to the standard static DEA models-they identify an optimal path of adjustment for the input quantities, and provide a measure of the potential cost savings that result from recognising the costs of adjusting input quantities towards the optimal point. The new models are illustrated using data relating to a chain of 35 retail department stores in Chile. The empirical results illustrate the wealth of information that can be derived from these models, and clearly show that static models overstate potential cost savings when adjustment costs are non-zero.

Demonstration of a simple entangling optical gate and its use in bell-state analysis

We demonstrate a new architecture for an optical entangling gate that is significantly simpler than previous realizations, using partially polarizing beam splitters so that only a single optical mode-matching condition is required. We demonstrate operation of a controlled-z gate in both continuous-wave and pulsed regimes of operation, fully characterizing it in each case using quantum process tomography. We also demonstrate a fully resolving, nondeterministic optical Bell-state analyzer based on this controlled-z gate. This new architecture is ideally suited to guided optics implementations of optical gates.

An optimal sequential procedure for a buying-selling problem with independent observations

We consider a buying-selling problem when two stops of a sequence of independent random variables are required. An optimal stopping rule and the value of a game are obtained.

Physical activity and strength of the femoral neck during the adolescent growth spurt: A longitudinal analysis

Loading of the femoral neck (FN) is dominated by bending and compressive stresses. We hypothesize that adaptation of the FN to physical activity would be manifested in the cross-sectional area (CSA) and section modulus (Z) of bone, indices of axial and bending strength, respectively. We investigated the influence of physical activity on bone strength during adolescence using 7 years of longitudinal data from 109 boys and 121 girls from the Saskatchewan Paediatric Bone and Mineral Accrual Study (PBMAS). Physical activity data (PAC-Q physical activity inventory) and anthropometric measurements were taken every 6 months and DXA bone scans were measured annually (Hologic QDR2000, array mode). We applied hip structural analysis to derive strength and geometric indices of the femoral neck using DXA scans. To control for maturation, we determined a biological maturity age defined as years from age at peak height velocity (APHV). To account for the repeated measures within individual nature of longitudinal data, multilevel random effects regression analyses were used to analyze the data. When biological maturity age and body size (height and weight) were controlled, in both boys and girls, physical activity was a significant positive independent predictor of CSA and Z of the narrow region of the femoral neck (P < 0.05). There was no independent effect of physical activity on the subperiosteal width of the femoral neck. When leg length and leg lean mass were introduced into the random effects models to control for size and muscle mass of the leg (instead of height and weight), all significant effects of physical activity disappeared. Even among adolescents engaged in normal levels of physical activity, the statistically significant relationship between physical activity and indices of bone strength demonstrate that modifiable lifestyle factors like exercise play an important role in optimizing bone strength during the growing years. Physical activity differences were explained by the interdependence between activity and lean mass considerations. Physical activity is important for optimal development of bone strength. (c) 2005 Elsevier Inc. All rights reserved.

Investigations into an optimal transmission scheme for a MIMO system operating in a ricain fading environment

This paper describes investigations into an optimal transmission scheme for a multiple input multiple output (MIMO) system operating in a Rician fading environment. The considerations are reduced to determining a covariance matrix of transmitted signals which maximizes the MIMO capacity under the condition that the receiver has perfect knowledge of the channel while the transmitter has the information about selected statistical quantities which are measured at the receiver. An optimal covariance matrix, which requires information of the Rice factor and the signal to noise ratio, is determined. The transmission scheme relying on the choice of the proposed covariance matrix outperforms the other transmission schemes which were reported earlier in the literature. The proposed scheme realizes an upper bound limit for the MIMO capacity under arbitrary Rician fading conditions. ©2005 IEEE

Optimal design of a regenerative dynamic dynamometer using genetic algorithms

This paper presents an approach for optimal design of a fully regenerative dynamic dynamometer using genetic algorithms. The proposed dynamometer system includes an energy storage mechanism to adaptively absorb the energy variations following the dynamometer transients. This allows the minimum power electronics requirement at the mains power supply grid to compensate for the losses. The overall dynamometer system is a dynamic complex system and design of the system is a multi-objective problem, which requires advanced optimisation techniques such as genetic algorithms. The case study of designing and simulation of the dynamometer system indicates that the genetic algorithm based approach is able to locate a best available solution in view of system performance and computational costs.

Gaussian regression and optimal finite dimensional linear models

The problem of regression under Gaussian assumptions is treated generally. The relationship between Bayesian prediction, regularization and smoothing is elucidated. The ideal regression is the posterior mean and its computation scales as O(n³), where n is the sample size. We show that the optimal m-dimensional linear model under a given prior is spanned by the first m eigenfunctions of a covariance operator, which is a trace-class operator. This is an infinite dimensional analogue of principal component analysis. The importance of Hilbert space methods to practical statistics is also discussed.