Motor unit synchronization measured by cross-correlation is not influenced by short-term strength training of a hand muscle

The purpose of the study was to quantify the strength of motor unit synchronization and coherence from pairs of concurrently active motor units before and after short-term (4–8 weeks) strength training of the left first dorsal interosseous (FDI) muscle. Five subjects (age 24.8 ± 4.3 years) performed a training protocol three times/week that consisted of six sets of ten maximal isometric index finger abductions, whereas three subjects (age 27.3 ± 6.7 years) acted as controls. Motor unit activity was recorded from pairs of intramuscular electrodes in the FDI muscle with two separate motor unit recording sessions obtained before and after strength training (trained group) or after 4 weeks of normal daily activities that did not involve training (control group). The training intervention resulted in a 54% (45.2 ± 8.3 to 69.5 ± 13.8 N, P = 0.001) increase in maximal index finger abduction force, whereas there was no change in strength in the control group. A total of 163 motor unit pairs (198 single motor units) were examined in both subject groups, with 52 motor unit pairs obtained from 10 recording sessions before training and 51 motor unit pairs from 10 recording sessions after training. Using the cross-correlation procedure, there was no change in the strength of motor unit synchronization following strength training (common input strength index; 0.71 ± 0.41 to 0.67 ± 0.43 pulses/s). Furthermore, motor unit coherence z scores at low (0–10 Hz; 3.9 ± 0.3 before to 4.4 ± 0.4 after) or high (10–30 Hz; 1.7 ± 0.1 before to 1.9 ± 0.1 after) frequencies were not influenced by strength training. These motor unit data indicate that increases in strength following several weeks of training a hand muscle are not accompanied by changes in motor unit synchronization or coherence, suggesting that these features of correlated motor unit activity are not important in the expression of muscle strength.

A new blind signal separation algorithm for instantaneous MIMO system

We address the problem of adaptive blind source separation (BSS) from instantaneous multi-input multi-output (MIMO) channels. In this paper, we propose a new constant modulus (CM)-based algorithm which employ nonlinear function as the de-correlation term. Moreover, it is shown by theoretical analysis that the proposed algorithm has less mean square error (MSE), i.e., better separation performance, in steady state than the cross-correlation and constant modulus algorithm (CC-CMA). Numerical simulations show the effectiveness of the proposed result.

A generalized data windowing scheme for adaptive conjugate gradient algorithms

The performance of the modified adaptive conjugate gradient (CG) algorithms based on the iterative CG method for adaptive filtering is highly related to the ways of estimating the correlation matrix and the cross-correlation vector. The existing approaches of implementing the CG algorithms using the data windows of exponential form or sliding form result in either loss of convergence or increase in misadjustment. This paper presents and analyzes a new approach to the implementation of the CG algorithms for adaptive filtering by using a generalized data windowing scheme. For the new modified CG algorithms, we show that the convergence speed is accelerated, the misadjustment and tracking capability comparable to those of the recursive least squares (RLS) algorithm are achieved. Computer simulations demonstrated in the framework of linear system modeling problem show the improvements of the new modifications.

Blind separation of mutually correlated sources using precoders

This paper studies the problem of blind source separation (BSS) from instantaneous mixtures with the assumption that the source signals are mutually correlated.We propose a novel approach to BSS by using precoders in transmitters.We show that if the precoders are properly designed, some cross-correlation coefficients of the coded signals can be forced to be zero at certain time lags. Then, the unique correlation properties of the coded signals can be exploited in receiver to achieve source separation. Based on the proposed precoders, a subspace-based algorithm is derived for the blind separation of mutually correlated sources. The effectiveness of the algorithm is illustrated by simulation examples.

Model-based character recognition in low resolution

We propose a combined character separation and recognition approach for low-resolution images of alphanumeric text. By synthesising the image formation process a set of low-resolution templates is created for each character. Cluster algorithms and normalised cross-correlation are then applied to match these templates and thereby allowing both character separation and recognition to be achieved at the same time. Thus characters are recognised using their low-resolution appearance only without applying image enhancement methods. Experiments showed that this approach is able to recognise low-resolution alphanumeric text of down to 5 pixels in size.

Predicting psychological and subjective well-being from personality: incremental prediction from 30 facets over the Big 5

This study investigated the relationship between the Big 5, measured at factor and facet levels, and dimensions of both psychological and subjective well-being. Three hundred and thirty-seven participants completed the 30 Facet International Personality Item Pool Scale, Satisfaction with Life Scale, Positive and Negative Affectivity Schedule, and Ryff’s Scales of Psychological Well-Being. Cross-correlation decomposition presented a parsimonious picture of how well-being is related to personality factors. Incremental facet prediction was examined using double-adjusted r2 confidence intervals and semi-partial correlations. Incremental prediction by facets over factors ranged from almost nothing to a third more variance explained, suggesting a more modest incremental prediction than presented in the literature previously. Examination of semi-partial correlations controlling for factors revealed a small number of important facet-well-being correlations. All data and R analysis scripts are made available in an online repository.

Robust optimal motion cueing algorithm based on the linear quadratic regulator method and a genetic algorithm

The aim of this paper is to design and develop an optimal motion cueing algorithm (MCA) based on the genetic algorithm (GA) that can generate high-fidelity motions within the motion simulator's physical limitations. Both, angular velocity and linear acceleration are adopted as the inputs to the MCA for producing the higher order optimal washout filter. The linear quadratic regulator (LQR) method is used to constrain the human perception error between the real and simulated driving tasks. To develop the optimal MCA, the latest mathematical models of the vestibular system and simulator motion are taken into account. A reference frame with the center of rotation at the driver's head to eliminate false motion cues caused by rotation of the simulator to the translational motion of the driver's head as well as to reduce the workspace displacement is employed. To improve the developed LQR-based optimal MCA, a new strategy based on optimal control theory and the GA is devised. The objective is to reproduce a signal that can follow closely the reference signal and avoid false motion cues by adjusting the parameters from the obtained LQR-based optimal washout filter. This is achieved by taking a series of factors into account, which include the vestibular sensation error between the real and simulated cases, the main dynamic limitations, the human threshold limiter in tilt coordination, the cross correlation coefficient, and the human sensation error fluctuation. It is worth pointing out that other related investigations in the literature normally do not consider the effects of these factors. The proposed optimized MCA based on the GA is implemented using the MATLAB/Simulink software. The results show the effectiveness of the proposed GA-based method in enhancing human sensation, maximizing the reference shape tracking, and reducing the workspace usage.

Economic growth and carbon emissions

In this paper, we investigate the dynamic relationship between economic growth and carbon dioxide (CO2) emissions for 181 countries. We propose a new approach based on the cross-correlation estimates to understand how economic growth and CO2 emissions are related. Our proposal is that if there is a positive cross-correlation between the current level of income and the past level of CO2 emissions and a negative cross-correlation between the current level of income and the future CO2 emissions, then CO2 emissions will decline with an increase in income over time, consistent with the environmental Kuznets curve (EKC) hypothesis. Our main findings can be summarized as follows. First, for 21 out of 181 countries (12%), there is clear evidence supporting the EKC hypothesis. Second, we ask whether a rise in income reduces emissions in the future. We find that for 49 countries (27%), income growth will reduce emissions in the future.

A new semi-automated method for assessing avian acoustic networks reveals that juvenile and adult zebra finches have separate calling networks

Social networks are often inferred from spatial associations, but other parameters like acoustic communication are likely to play a central role in within group interactions. However, it is currently difficult to determine which individual initiates vocalizations, or who responds to whom. To this aim, we designed a method that allows analyzing group vocal network while controlling for spatial networks, by positioning each group member in equidistant individual cages and analyzing continuous vocal interactions semi-automatically. We applied this method to two types of zebra finch groups, composed of either two adult females and two juveniles, or four young adults (juveniles from the first groups). Young often co-occur in the same social group as adults but are likely to have a different social role, which may be reflected in their vocal interactions. Therefore, we tested the hypothesis that the social structure of the group influences the parameters of the group vocal network. We found that groups including juveniles presented periods with higher level of activity than groups composed of young adults. Using two types of analyses (Markov analysis and cross-correlation), we showed that juveniles as well as adults were more likely to respond to individuals of their own age-class (i.e. to call one after another, in terms of turn-taking, and within a short time-window, in terms of time delay). When juveniles turned into adulthood, they showed adult characteristics of vocal patterns. Together our results suggest that vocal behavior changes during ontogeny, and individuals are more strongly connected with individuals of the same age-class within acoustic networks.

Cross-national agreement on disability weights:the Eurpoean disability weights project

Background: Disability weights represent the relative severity of disease stages to be incorporated in summary measures of population health. The level of agreement on disability weights in Western European countries was investigated with different valuation methods.

Methods: Disability weights for fifteen disease stages were elicited empirically in panels of health care professionals or non-health care professionals with an academic background following a strictly standardised procedure. Three valuation methods were used: a visual analogue scale (VAS); the time trade-off technique (TTO); and the person trade-off technique (PTO). Agreement among England, France, the Netherlands, Spain, and Sweden on the three disability weight sets was analysed by means of an intraclass correlation coefficient (ICC) in the framework of generalisability theory. Agreement among the two types of panels was similarly assessed.

Results: A total of 232 participants were included. Similar rankings of disease stages across countries were found with all valuation methods. The ICC of country agreement on disability weights ranged from 0.56 [95% CI, 0.52–0.62] with PTO to 0.72 [0.70–0.74] with VAS and 0.72 [0.69–0.75] with TTO. The ICC of agreement between health care professionals and non-health care professionals ranged from 0.64 [0.58–0.68] with PTO to 0.73 [0.71–0.75] with VAS and 0.74 [0.72–0.77] with TTO.

Conclusions: Overall, the study supports a reasonably high level of agreement on disability weights in Western European countries with VAS and TTO methods, which focus on individual preferences, but a lower level of agreement with the PTO method, which focuses more on societal values in resource allocation.

Learning style drift : correlation between built environment students' learning styles and the learning styles of their teachers

This paper focuses on the results of a cross-curriculum learning style survey conducted in an Australian School of Architecture and Building as part of an ongoing project aimed at resolving the learning difficulties of students collaborating in multi-disciplinary and multicultural team assignments. The research was conducted to determine how learning style differences in heterogeneous design teams might be addressed through pedagogy. We will argue that the likelihood of and reasons for learning style fluidity in student design cohorts needs determining if learning style theory is to provide a workable model for informing the teaching of design.
In light of evidence in student cohorts of learning style changes as students progress through their studies (Tucker, 2007), this research discusses one explanation of what appears to belearning style fluidity in architecture student cohorts. If, as prior research has indicated, the learning styles of academics are quite different from practitioners, evidence of a learning style drift in built environment students towards the predominant learning styles of their design teachers might suggest that students are learning how to be academics rather than practitioners. This, of course, might have serious implications for built environment teaching and for practice.

Waist circumference, waist-hip ratio and BMI and their correlation with cardiovascular risk factors in Australian adults

Objectives. To compare body mass index (BMI), waist circumference and waist–hip ratio (WHR) as indices of obesity and assess the respective associations with type 2 diabetes, hypertension and dyslipidaemia.

Design and setting. A national sample of 11 247 Australians aged ≥25 years was examined in 2000 in a cross-sectional survey.

Main outcome measures. The examination included a fasting blood sample, standard 2-h 75-g oral glucose tolerance test, blood pressure measurements and questionnaires to assess treatment for dyslipidaemia and hypertension. BMI, waist circumference and WHR were measured to assess overweight and obesity.

Results. The prevalence of obesity amongst Australian adults defined by BMI, waist circumference and WHR was 20.8, 30.5 and 15.8% respectively. The unadjusted odds ratio for the fourth vs. first quartile of each obesity measurement showed that WHR had the strongest relationship with type 2 diabetes, dyslipidaemia (women only) and hypertension. Following adjustment for age, however, there was little difference between the three measures of obesity, with the possible exceptions of hypertension in women, where BMI had a stronger association, and dyslipidaemia in women and type 2 diabetes in men, where WHR was marginally superior.

Conclusions. Waist circumference, BMI and WHR identified different proportions of the population, as measured by both prevalence of obesity and cardiovascular disease (CVD) risk factors. Whilst WHR had the strongest correlations with CVD risk factors before adjustment for age, the three obesity measures performed similarly after adjustment for age. Given the difficulty of using age-adjusted associations in the clinical setting, these results suggest that given appropriate cut-off points, WHR is the most useful measure of obesity to use to identify individuals with CVD risk factors.