Data analysis in multiple-frequency bioelectrical impedance analysis

The performance of three analytical methods for multiple-frequency bioelectrical impedance analysis (MFBIA) data was assessed. The methods were the established method of Cole and Cole, the newly proposed method of Siconolfi and co-workers and a modification of this procedure. Method performance was assessed from the adequacy of the curve fitting techniques, as judged by the correlation coefficient and standard error of the estimate, and the accuracy of the different methods in determining the theoretical values of impedance parameters describing a set of model electrical circuits. The experimental data were well fitted by all curve-fitting procedures (r = 0.9 with SEE 0.3 to 3.5% or better for most circuit-procedure combinations). Cole-Cole modelling provided the most accurate estimates of circuit impedance values, generally within 1-2% of the theoretical values, followed by the Siconolfi procedure using a sixth-order polynomial regression (1-6% variation). None of the methods, however, accurately estimated circuit parameters when the measured impedances were low (<20 Omega) reflecting the electronic limits of the impedance meter used. These data suggest that Cole-Cole modelling remains the preferred method for the analysis of MFBIA data.

Better prediction of protein contact number using a support vector regression analysis of amino acid sequence

Background: Protein tertiary structure can be partly characterized via each amino acid's contact number measuring how residues are spatially arranged. The contact number of a residue in a folded protein is a measure of its exposure to the local environment, and is defined as the number of C-beta atoms in other residues within a sphere around the C-beta atom of the residue of interest. Contact number is partly conserved between protein folds and thus is useful for protein fold and structure prediction. In turn, each residue's contact number can be partially predicted from primary amino acid sequence, assisting tertiary fold analysis from sequence data. In this study, we provide a more accurate contact number prediction method from protein primary sequence. Results: We predict contact number from protein sequence using a novel support vector regression algorithm. Using protein local sequences with multiple sequence alignments (PSI-BLAST profiles), we demonstrate a correlation coefficient between predicted and observed contact numbers of 0.70, which outperforms previously achieved accuracies. Including additional information about sequence weight and amino acid composition further improves prediction accuracies significantly with the correlation coefficient reaching 0.73. If residues are classified as being either contacted or non-contacted, the prediction accuracies are all greater than 77%, regardless of the choice of classification thresholds. Conclusion: The successful application of support vector regression to the prediction of protein contact number reported here, together with previous applications of this approach to the prediction of protein accessible surface area and B-factor profile, suggests that a support vector regression approach may be very useful for determining the structure-function relation between primary sequence and higher order consecutive protein structural and functional properties.

Repeatability of maximal voluntary force and of surface EMG variables during voluntary isometric contraction of quadriceps muscles in healthy subjects

The repeatability of initial values and rate of change of EMG signal mean spectral frequency (MNF), average rectified values (ARV), muscle fiber conduction velocity (CV) and maximal voluntary contraction (MVC) was investigated in the vastus medialis obliquus (VMO) and vastus lateralis (VL) muscles of both legs of nine healthy male subjects during voluntary, isometric contractions sustained for 50 s at 50% MVC. The values of MVC were recorded for both legs three times on each day and for three subsequent days, while the EMG signals have been recorded twice a day for three subsequent days. The degree of repeatability was investigated using the Fisher test based upon the ANalysis Of VAriance (ANOVA), the Standard Error of the Mean (SEM) and the Intraclass Correlation Coefficient (ICC). Data collected showed a high level of repeatability of MVC measurement (normalized SEM from 1.1% to 6.4% of the mean). MNF and ARV initial values also showed a high level of repeatability (ICC > 70% for all muscles and legs except right VMO). At 50% MVC level no relevant pattern of fatigue was observed for the VMO and VL muscles, suggesting that other portions of the quadriceps might have contributed to the generated effort. These observations seem to suggest that in the investigation of muscles belonging to a multi-muscular group at submaximal level, the more selective electrically elicited contractions should be preferred to voluntary contractions. (C) 2001 Elsevier Science Ltd. All rights reserved.

Application of the Williams-Landel-Ferry model to the viscosity-temperature relationship of Australian honeys

The rheological behaviour of nine unprocessed Australian honeys was investigated for the applicability of the Williams-Landel-Ferry (WLF) model. The viscosity of the honeys was obtained over a range of shear rates (0.01-40 s(-1)) from 2degrees to 40 degreesC, and all the honeys exhibited Newtonian behaviour with viscosity reducing as the temperature was increased. The honeys with high moisture were of lower viscosity, The glass transition temperatures of the honeys, as measured with a differential scanning calorimeter (DSC), ranged from -40degrees to -46 degreesC, and four models (WLF. Arrhenius, Vogel-Tammann-Fulcher (VTF), and power-law) were investigated to describe the temperature dependence of the viscosity. The WLF was the most suitable and the correlation coefficient averaged 0.999 +/- 0.0013 as against 0.996 +/- 0.0042 for the Arrhenius model while the mean relative deviation modulus was 0-12% for the WLF model and 10-40% for the Arrhenius one. With the universal values for the WLF constants, the temperature dependence of the viscosity was badly predicted. From non-linear regression analysis, the constants of the WLF models for the honeys were obtained (C-1 = 13.7-21.1: C-2 = 55.9-118.7) and are different from the universal values. These WLF constants will be valuable for adequate modeling of the rheology of the honeys, and they can be used to assess the temperature sensitivity of the honeys. (C) 2002 Elsevier Science Ltd. All rights reserved.

Long-range automaton models of earthquakes: Power-law accelerations, correlation evolution, and mode-switching

We introduce a conceptual model for the in-plane physics of an earthquake fault. The model employs cellular automaton techniques to simulate tectonic loading, earthquake rupture, and strain redistribution. The impact of a hypothetical crustal elastodynamic Green's function is approximated by a long-range strain redistribution law with a r(-p) dependance. We investigate the influence of the effective elastodynamic interaction range upon the dynamical behaviour of the model by conducting experiments with different values of the exponent (p). The results indicate that this model has two distinct, stable modes of behaviour. The first mode produces a characteristic earthquake distribution with moderate to large events preceeded by an interval of time in which the rate of energy release accelerates. A correlation function analysis reveals that accelerating sequences are associated with a systematic, global evolution of strain energy correlations within the system. The second stable mode produces Gutenberg-Richter statistics, with near-linear energy release and no significant global correlation evolution. A model with effectively short-range interactions preferentially displays Gutenberg-Richter behaviour. However, models with long-range interactions appear to switch between the characteristic and GR modes. As the range of elastodynamic interactions is increased, characteristic behaviour begins to dominate GR behaviour. These models demonstrate that evolution of strain energy correlations may occur within systems with a fixed elastodynamic interaction range. Supposing that similar mode-switching dynamical behaviour occurs within earthquake faults then intermediate-term forecasting of large earthquakes may be feasible for some earthquakes but not for others, in alignment with certain empirical seismological observations. Further numerical investigation of dynamical models of this type may lead to advances in earthquake forecasting research and theoretical seismology.

Reliability of electromyographic and torque measures during isometric axial rotation exertions of the trunk

Objective: The aim of the present study was to investigate the between-days reliability of electromyographic (EMG) measurement of 6 bilateral trunk muscles and also the torque output in 3 planes during isometric right and left axial rotation at different exertion levels. Methods: Ten healthy subjects performed isometric right and left axial rotation at 100, 70, 50 and 30% maximum voluntary contractions in two testing sessions at least 7 days apart. EMG amplitude and frequency analyses of the recorded surface EMG signals were performed for rectus abdominis, external oblique, internal oblique, latissimus dorsi, iliocostalis lumborum and multifidus bilaterally. The primary torque in the transverse plane and the coupling torques in sagittal and coronal planes were measured. Results: For both EMG amplitude and frequency values, good (intraclass correlation coefficient, ICC = 0.75-0.89) to excellent (ICC greater than or equal to 0.90) reliability was found in the 6 trunk muscles at different exertion levels during axial rotation. The reliability of both maximal isometric axial rotation torque and coupling torques in sagittal and coronal planes were found to be excellent (ICC greater than or equal to 0.93). Conclusions: Good to excellent reliability of EMG measures of trunk muscles and torque measurements during isometric axial rotation was demonstrated. This provides further confidence of using EMG and triaxial torque assessment as outcome measures in rehabilitation and in the evaluation of the human performance in the work place. (C) 2003 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Advantage of single-trial models for response to selection in wheat breeding multi-environment trials

An investigation was conducted to evaluate the impact of experimental designs and spatial analyses (single-trial models) of the response to selection for grain yield in the northern grains region of Australia (Queensland and northern New South Wales). Two sets of multi-environment experiments were considered. One set, based on 33 trials conducted from 1994 to 1996, was used to represent the testing system of the wheat breeding program and is referred to as the multi-environment trial (MET). The second set, based on 47 trials conducted from 1986 to 1993, sampled a more diverse set of years and management regimes and was used to represent the target population of environments (TPE). There were 18 genotypes in common between the MET and TPE sets of trials. From indirect selection theory, the phenotypic correlation coefficient between the MET and TPE single-trial adjusted genotype means [r(p(MT))] was used to determine the effect of the single-trial model on the expected indirect response to selection for grain yield in the TPE based on selection in the MET. Five single-trial models were considered: randomised complete block (RCB), incomplete block (IB), spatial analysis (SS), spatial analysis with a measurement error (SSM) and a combination of spatial analysis and experimental design information to identify the preferred (PF) model. Bootstrap-resampling methodology was used to construct multiple MET data sets, ranging in size from 2 to 20 environments per MET sample. The size and environmental composition of the MET and the single-trial model influenced the r(p(MT)). On average, the PF model resulted in a higher r(p(MT)) than the IB, SS and SSM models, which were in turn superior to the RCB model for MET sizes based on fewer than ten environments. For METs based on ten or more environments, the r(p(MT)) was similar for all single-trial models.

Prediction of protein B-factor profiles

The polypeptide backbones and side chains of proteins are constantly moving due to thermal motion and the kinetic energy of the atoms. The B-factors of protein crystal structures reflect the fluctuation of atoms about their average positions and provide important information about protein dynamics. Computational approaches to predict thermal motion are useful for analyzing the dynamic properties of proteins with unknown structures. In this article, we utilize a novel support vector regression (SVR) approach to predict the B-factor distribution (B-factor profile) of a protein from its sequence. We explore schemes for encoding sequences and various settings for the parameters used in SVR. Based on a large dataset of high-resolution proteins, our method predicts the B-factor distribution with a Pearson correlation coefficient (CC) of 0.53. In addition, our method predicts the B-factor profile with a CC of at least 0.56 for more than half of the proteins. Our method also performs well for classifying residues (rigid vs. flexible). For almost all predicted B-factor thresholds, prediction accuracies (percent of correctly predicted residues) are greater than 70%. These results exceed the best results of other sequence-based prediction methods. (C) 2005 Wiley-Liss, Inc.

Reply to "Comment on 'Signal correlation between two normal-mode helical antennas for diversity reception in a multipath environment'"

This comment points out an inaccurate formula relating the signal correlation coefficient to the mutual impedance and corrects it. © 2005 IEEE.

A Nonstationary Model of Newborn EEG

The detection of seizure in the newborn is a critical aspect of neurological research. Current automatic detection techniques are difficult to assess due to the problems associated with acquiring and labelling newborn electroencephalogram (EEG) data. A realistic model for newborn EEG would allow confident development, assessment and comparison of these detection techniques. This paper presents a model for newborn EEG that accounts for its self-similar and non-stationary nature. The model consists of background and seizure sub-models. The newborn EEG background model is based on the short-time power spectrum with a time-varying power law. The relationship between the fractal dimension and the power law of a power spectrum is utilized for accurate estimation of the short-time power law exponent. The newborn EEG seizure model is based on a well-known time-frequency signal model. This model addresses all significant time-frequency characteristics of newborn EEG seizure which include; multiple components or harmonics, piecewise linear instantaneous frequency laws and harmonic amplitude modulation. Estimates of the parameters of both models are shown to be random and are modelled using the data from a total of 500 background epochs and 204 seizure epochs. The newborn EEG background and seizure models are validated against real newborn EEG data using the correlation coefficient. The results show that the output of the proposed models has a higher correlation with real newborn EEG than currently accepted models (a 10% and 38% improvement for background and seizure models, respectively).

Determination of pindolol enantiomers in human plasma and urine by simple liquid-liquid extraction and high-performance liquid chromatography

A simple method for the measurement of pindolol enantiomers by HPLC is presented. Alkalinized serum or urine is extracted with ethyl acetate and the residue remaining after evaporation of the organic layer is then derivatised with (S)-(-)-alpha-methylbenzyl isocyanate. The diastereoisomers of derivatised pindolol and metoprolol (internal standard) are separated by high-performance liquid chromatography (HPLC) using a C-18 silica column and detected using fluorescence (excitation lambda: 215 nm, emission lambda: 320 nm). The assay displays reproducible linearity for pindolol enantiomers with a correlation coefficient of r(2) greater than or equal to 0.998 over the concentration range 8-100 ng ml(-1) for plasma and 0.1-2.5 mu g ml(-1) for urine. The coefficient of variation for accuracy and precision of the quality control samples for both plasma and urine are consistently

Development, reliability, and concurrent validity of the modified inventory of potential reconstructive needs

Documentation of burn sequelae can be a difficult and time-consuming task. To date a reliable and systematic format for recording postburn trauma is lacking. The purpose of this research was two-fold: first, to develop a Modified Inventory of Potential Reconstructive Needs from the original Inventory of Potential Reconstructive Needs to allow methodical documentation of functional and cosmetic burn sequelae in all body surface areas of children with burns and, second, to establish interrater reliability and concurrent validity of the instrument, thus allowing its clinical application. Two raters scored the Modified Inventory of Potential Reconstructive Needs on 41 children with a range of burns types and severity. Excellent interrater reliability was demonstrated for both total (intraclass correlation coefficient = 0.996) and subsection inventory scores. Concurrent validity was also established with total scores showing strong positive correlations (0.73-0.76) with three indicators of burn severity. These findings provide initial support for the tool's clinical applicability, particularly in relation to rehabilitative planning and documentation.

Adolescents' perceptions of social status: Development and evaluation of a new indicator

Objective. Eliminating health disparities, including those that are a result of socioeconomic status (SES), is one of the overarching goals of Healthy People 2010. This article reports on the development of a new, adolescent-specific measure of subjective social status (SSS) and on initial exploratory analyses of the relationship of SSS to adolescents' physical and psychological health. Methods. A cross-sectional study of 10 843 adolescents and a subsample of 166 paired adolescent/mother dyads who participated in the Growing Up Today Study was conducted. The newly developed MacArthur Scale of Subjective Social Status (10-point scale) was used to measure SSS. Paternal education was the measure of SES. Indicators of psychological and physical health included depressive symptoms and obesity, respectively. Linear regression analyses determined the association of SSS to depressive symptoms, and logistic regression determined the association of SSS to overweight and obesity, controlling for sociodemographic factors and SES. Results. Mean society ladder ranking, a subjective measure of SES, was 7.2 ± 1.3. Mean community ladder ranking, a measure of perceived placement in the school community, was 7.6 ± 1.7. Reliability of the instrument was excellent: the intraclass correlation coefficient was 0.73 for the society ladder and 0.79 for the community ladder. Adolescents had higher society ladder rankings than their mothers (µteen = 7.2 ± 1.3 vs µmom = 6.8 ± 1.2; P = .002). Older adolescents' perceptions of familial placement in society were more closely correlated with maternal subjective perceptions of placement than those of younger adolescents (Spearman's rhoteens

A proposed maceral index to predict combustion behavior of coal

To predict the combustion performance in pulverized coal-fired boilers, this paper examines existing indices and develops a maceral index (MI). These indices were compared with the data of 68 coals and blends in a range of the mean vitrinite reflectance from 0.25 to 1.63. The results showed that the fuel ratio and the mean vitrinite reflectance could qualitatively indicate the burnout of the coals and blends. The new MI, MI = L + V/R-2/I-1.25(HV/30)(2.5), provides a useful correlation for the burnout of the coals and blends. The correlation coefficient (I-) is 0.982 for the EER data, and 0.808 for the ACIRL data. The MI also has potential to correlate ignition and flame stability of the coals and blends. The MI predicts the burnout better than the other indices. (C) 2001 Elsevier Science Ltd. All rights reserved.

Repeatability of surface EMG variables in the sternocleidomastoid and anterior scalene muscles

In this study we examined the repeatability and reliability of the surface electromyographic (sEMG) signal mean frequency (MNF), average rectified value (ARV) and conduction velocity (CV) measured for the sternocleidomastoid (SCM) and the anterior scalene (AS) muscles in nine healthy volunteers during 15-s isometric cervical flexion contractions at 50% of the maximal voluntary contraction level over 3 non-consecutive days. Repeatability and reliability estimates were obtained for the initial values and rates of change of each sEMG variable by using both the Intraclass Correlation Coefficient (ICC) and the normalised standard error of the mean (nSEM). Results from SCM indicated good levels of repeatability for the initial value and slope of ARV (ICC > 65%). For the AS, high levels of repeatability were identified for the initial value of MNF (ICC > 70%) and the slope of ARV (ICC > 75%). Values of nSEM in the range 2.8-7.2% were obtained for the initial values of MNF and CV for both SCM and AS, indicating clinically acceptable measurement precision. The low value obtained for the nSEM of the initial value of MNF for the AS, in combination with the high ICC, indicates that of all of the variables examined, this variable could offer the best normative index to distinguish between subjects with and without neck pain, and represents the sEMG variable of choice for future evaluation purposes.