A novel continuous forward algorithm for RBF neural modelling

A continuous forward algorithm (CFA) is proposed for nonlinear modelling and identification using radial basis function (RBF) neural networks. The problem considered here is simultaneous network construction and parameter optimization, well-known to be a mixed integer hard one. The proposed algorithm performs these two tasks within an integrated analytic framework, and offers two important advantages. First, the model performance can be significantly improved through continuous parameter optimization. Secondly, the neural representation can be built without generating and storing all candidate regressors, leading to significantly reduced memory usage and computational complexity. Computational complexity analysis and simulation results confirm the effectiveness.

Reliability and Validity of the Child Health QuestionnairePF-50 for European Children with Cerebral Palsy

Objective: To evaluate the psychometric performance of the Child Health Questionnaire (CHQ) in children with cerebral palsy (CP).
Method: 818 parents of children with CP, aged 8–12 from nine regions of Europe completed the CHQ (parent form 50 items). Functional abilities were classified using the five-level Gross Motor Function Classification Scheme (Levels I–III as ambulant; Level IV–V as nonambulant CP).
Results: Ceiling effects were observed for a number of subscales and summary scores across all Gross Motor Function Classification System levels, whilst floor effects occurred only in the physical functioning scale (Level V CP). Reliability was satisfactory overall. Confirmatory factor analysis (CFA) revealed a seven-factor structure for the total sample of children with CP but with different factor structures for ambulant and nonambulant children.
Conclusion: The CHQ has limited applicability in children with CP, although with judicious use of certain domains for ambulant and nonambulant children can provide useful and comparable data about child health status for descriptive purposes.

Adaptive data echo cancellation using cost function adaptation

For a digital echo canceller it is desirable to reduce the adaptation time, during which the transmission of useful data is not possible. LMS is a non-optimal algorithm in this case as the signals involved are statistically non-Gaussian. Walach and Widrow (IEEE Trans. Inform. Theory 30 (2) (March 1984) 275-283) investigated the use of a power of 4, while other research established algorithms with arbitrary integer (Pei and Tseng, IEEE J. Selected Areas Commun. 12(9)(December 1994) 1540-1547) or non-quadratic power (Shah and Cowan, IEE.Proc.-Vis. Image Signal Process. 142 (3) (June 1995) 187-191). This paper suggests that continuous and automatic, adaptation of the error exponent gives a more satisfactory result. The family of cost function adaptation (CFA) stochastic gradient algorithm proposed allows an increase in convergence rate and, an improvement of residual error. As special case the staircase CFA algorithm is first presented, then the smooth CFA is developed. Details of implementations are also discussed. Results of simulation are provided to show the properties of the proposed family of algorithms. (C) 2000 Elsevier Science B.V. All rights reserved.

The complex effects of the slow-releasing hydrogen sulfide donor GYY4137 in a model of acute joint inflammation and in human cartilage cells

The role of hydrogen sulfide (H2 S) in inflammation remains unclear with both pro- and anti-inflammatory actions of this gas described. We have now assessed the effect of GYY4137 (a slow-releasing H2 S donor) on lipopolysaccharide (LPS)-evoked release of inflammatory mediators from human synoviocytes (HFLS) and articular chondrocytes (HAC) in vitro. We have also examined the effect of GYY4137 in a complete Freund's adjuvant (CFA) model of acute joint inflammation in the mouse. GYY4137 (0.1-0.5 mM) decreased LPS-induced production of nitrite (NO2 (-) ), PGE2 , TNF-a and IL-6 from HFLS and HAC, reduced the levels and catalytic activity of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) and reduced LPS-induced NF-?B activation in vitro. Using recombinant human enzymes, GYY4137 inhibited the activity of COX-2, iNOS and TNF-a converting enzyme (TACE). In the CFA-treated mouse, GYY4137 (50 mg/kg, i.p.) injected 1 hr prior to CFA increased knee joint swelling while an anti-inflammatory effect, as demonstrated by reduced synovial fluid myeloperoxidase (MPO) and N-acetyl-ß-D-glucosaminidase (NAG) activity and decreased TNF-a, IL-1ß, IL-6 and IL-8 concentration, was apparent when GYY4137 was injected 6 hrs after CFA. GYY4137 was also anti-inflammatory when given 18 hrs after CFA. Thus, although GYY4137 consistently reduced the generation of pro-inflammatory mediators from human joint cells in vitro, its effect on acute joint inflammation in vivo depended on the timing of administration.

Bit erasure analysis of binary adders in quantum-dot cellular automata

As a post-CMOS technology, the incipient Quantum-dot Cellular Automata technology has various advantages. A key aspect which makes it highly desirable is low power dissipation. One method that is used to analyse power dissipation in QCA circuits is bit erasure analysis. This method has been applied to analyse previously proposed QCA binary adders. However, a number of improved QCA adders have been proposed more recently that have only been evaluated in terms of area and speed. As the three key performance metrics for QCA circuits are speed, area and power, in this paper, a bit erasure analysis of these adders will be presented to determine their power dissipation. The adders to be analysed are the Carry Flow Adder (CFA), Brent-Kung Adder (B-K), Ladner-Fischer Adder (L-F) and a more recently developed area-delay efficient adder. This research will allow for a more comprehensive comparison between the different QCA adder proposals. To the best of the authors' knowledge, this is the first time power dissipation analysis has been carried out on these adders.

The Prenatal Distress Questionnaire:An investigation of factor structure in a high risk population

Background: The Prenatal Distress Questionnaire (PDQ) is a short measure designed to assess specific worries and concerns related to pregnancy. The aim of this study was to confirm the factor structure of the PDQ in a group of pregnant women with a small for gestational age infant (< 10th centile). Methods: The first PDQ assessment for each of 337 pregnant women participating in the Prospective Observational Trial to Optimise paediatric health (PORTO) study was analysed. All women enrolled in the study were identified as having a small for gestational age foetus (< 10th centile), thus representing an 'elevated risk' group. Data were analysed using confirmatory factor analysis (CFA). Three models of the PDQ were evaluated and compared in the current study: a theoretical uni-dimensional measurement model, a bi-dimensional model, and a three-factor model solution. Results: The three-factor model offered the best fit to the data while maintaining sound theoretical grounds(χ² (51df) = 128.52; CFI = 0.97; TLI = 0.96; RMSEA = 0.07). Factor 1 contained items reflecting concerns about birth and the baby, factor 2 concerns about physical symptoms and body image and factor 3 concerns about emotions and relationships. Conclusions: CFA confirmed that the three-factor model provided the best fit, with the items in each factor reflecting the findings of an earlier exploratory data analysis. © 2013 Society for Reproductive and Infant Psychology.

Cost-Efficient Decimal Adder Design in Quantum-dot Cellular Automata

Applications that cannot tolerate the loss of accuracy that results from binary arithmetic demand hardware decimal arithmetic designs. Binary arithmetic in Quantum-dot cellular automata (QCA) technology has been extensively investigated in recent years. However, only limited attention has been paid to QCA decimal arithmetic. In this paper, two cost-efficient binary-coded decimal (BCD) adders are presented. One is based on the carry flow adder (CFA) using a conventional correction method. The other uses the carry look ahead (CLA) algorithm which is the first QCA CLA decimal adder proposed to date. Compared with previous designs, both decimal adders achieve better performance in terms of latency and overall cost. The proposed CFA-based BCD adder has the smallest area with the least number of cells. The proposed CLA-based BCD adder is the fastest with an increase in speed of over 60% when compared with the previous fastest decimal QCA adder. It also has the lowest overall cost with a reduction of over 90% when compared with the previous most cost-efficient design.

Psychometric evaluation of the Student Authorship Questionnaire: a confirmatory factor analysis approach

This research provides new insights into the measurement of students’ authorial identity and its potential for minimising the incidence of unintentional plagiarism by providing evidence about the psychometric properties of the Student Authorship Questionnaire (SAQ). Exploratory and confirmatory factor analyses (EFA and CFA) are employed to investigate the measurement properties of the scales which comprise the SAQ using data collected from accounting students. The results provide limited psychometric support in favour of the factorial structure of the SAQ and raise a number of questions regarding the instrument’s robustness and generalisability across disciplines. An alternative model derived from the EFA outperforms the SAQ model with regard to its psychometric properties. Explanations for these findings are proffered and avenues for future research suggested.

Testing the psychometric properties of Kidscreen-27 with Irish children of low socio-economic status

Background

Kidscreen-27 was developed as part of a cross-cultural European Union-funded project to standardise the measurement of children’s health-related quality of life. Yet, research has reported mixed evidence for the hypothesised 5-factor model, and no confirmatory factor analysis (CFA) has been conducted on the instrument with children of low socio-economic status (SES) across Ireland (Northern and Republic).

Method

The data for this study were collected as part of a clustered randomised controlled trial. A total of 663 (347 male, 315 female) 8–9-year-old children (M = 8.74, SD = .50) of low SES took part. A 5- and modified 7-factor CFA models were specified using the maximum likelihood estimation. A nested Chi-square difference test was conducted to compare the fit of the models. Internal consistency and floor and ceiling effects were also examined.

Results

CFA found that the hypothesised 5-factor model was an unacceptable fit. However, the modified 7-factor model was supported. A nested Chi-square difference test confirmed that the fit of the 7-factor model was significantly better than that of the 5-factor model. Internal consistency was unacceptable for just one scale. Ceiling effects were present in all but one of the factors.

Conclusions

Future research should apply the 7-factor model with children of low socio-economic status. Such efforts would help monitor the health status of the population.