A phase II multicentered, single-blind, randomized, controlled trial of the stroke self-management program

Background and Purpose—The benefits of chronic disease self-management programs for stroke survivors are uncertain because individuals with severe impairments have been excluded from previous research. We undertook a phase II randomized controlled trial to determine whether a self-management program designed for survivors (SSMP; 8 weeks) was safe and feasible compared to standard care (control) or a generic self-management program (generic; 6 weeks).
Methods—Stroke survivors were recruited from 7 South Australian hospitals via a letter or indirectly (eg, newspapers). Eligible participants were randomized at a 1:1:1 ratio of 50 per group. Primary outcomes were recruitment, participation, and participant safety. Secondary outcomes were positive and active engagement in life using the Health Education Impact Questionnaire and characteristics of quality of life and mood at 6 months from program completion.
Results—Of 315 people screened, 149 were eligible and 143 were randomized (48 SSMP, 47 generic, 48 control); mean age was 69 years (SD, 11) and 59% were female. Demographic features were similar between groups and 41% had severe cognitive impairment; 57% accessed the interventions, with 52% SSMP and 38% generic completing >50% of sessions (P=0.18). Thirty-two participants reported adverse events (7 control, 12 generic, 13 SSMP; P=0.3; 34% severe); however, none was attributable to the interventions. Potential benefits for improved mood were found.
Conclusions—SSMP was safe and feasible. Benefits of the stroke-specific program over the generic program included greater participation and completion rates. An efficacy trial is warranted given the forecast growth in the stroke population and improved survival trends.

Maximum contrast analysis for nonnegative blind source separation

In this paper, we propose a maximum contrast analysis (MCA) method for nonnegative blind source separation, where both the mixing matrix and the source signals are nonnegative. We first show that the contrast degree of the source signals is greater than that of the mixed signals. Motivated by this observation, we propose an MCA-based cost function. It is further shown that the separation matrix can be obtained by maximizing the proposed cost function. Then we derive an iterative determinant maximization algorithm for estimating the separation matrix. In the case of two sources, a closed-form solution exists and is derived. Unlike most existing blind source separation methods, the proposed MCA method needs neither the independence assumption, nor the sparseness requirement of the sources. The effectiveness of the new method is illustrated by experiments using X-ray images, remote sensing images, infrared spectral images, and real-world fluorescence microscopy images.

Time-frequency approach to underdetermined blind source separation

This paper presents a new time-frequency (TF) underdetermined blind source separation approach based on Wigner-Ville distribution (WVD) and Khatri-Rao product to separate N non-stationary sources from M(M <; N) mixtures. First, an improved method is proposed for estimating the mixing matrix, where the negative value of the auto WVD of the sources is fully considered. Then after extracting all the auto-term TF points, the auto WVD value of the sources at every auto-term TF point can be found out exactly with the proposed approach no matter how many active sources there are as long as N ≤ 2M-1. Further discussion about the extraction of auto-term TF points is made and finally the numerical simulation results are presented to show the superiority of the proposed algorithm by comparing it with the existing ones.

Maintenance N-acetyl cysteine treatment for bipolar disorder : a double-blind randomised placebo controlled trial

Background N-acetyl cysteine (NAC) is a glutathione precursor that has been shown to have antidepressant efficacy in a placebo-controlled trial. The current study aimed to investigate the maintenance effects of NAC following eight weeks of open-label treatment for bipolar disorder.

Method The efficacy of a double blind randomized placebo controlled trial of 2 g/day NAC as adjunct maintenance treatment for bipolar disorder was examined. Participants (n = 149) had a Montgomery Asberg Depression Rating Score of [greater than or equal to]12 at trial entry and, after eight weeks of open-label NAC treatment, were randomized to adjunctive NAC or placebo, in addition to treatment as usual. Participants (primarily outpatients) were recruited through public and private services and through newspaper advertisements. Time to intervention for a mood episode was the primary endpoint of the study, and changes in mood symptoms, functionality and quality of life measures were secondary outcomes.

Results There was a substantial decrease in symptoms during the eight-week open-label NAC treatment phase. During the subsequent double-blind phase, there was minimal further change in outcome measures with scores remaining low. Consequently, from this low plateau, between-group differences did not emerge on recurrence, clinical functioning or quality of life measures.

Conclusions There were no significant between-group differences in recurrence or symptomatic outcomes during the maintenance phase of the trial; however, these findings may be confounded by limitations. Trial Registration The trial was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12607000074493).

Underdetermined blind source separation by parallel factor analysis in time-frequency domain

This paper presents a new time-frequency approach to the underdetermined blind source separation using the parallel factor decomposition of third-order tensors. Without any constraint on the number of active sources at an auto-term time-frequency point, this approach can directly separate the sources as long as the uniqueness condition of parallel factor decomposition is satisfied. Compared with the existing two-stage methods where the mixing matrix should be estimated at first and then used to recover the sources, our approach yields better source separation performance in the presence of noise. Moreover, the mixing matrix can be estimated at the same time of the source separation process. Numerical simulations are presented to show the superior performance of the proposed approach to some of the existing two-stage blind source separation methods that use the time-frequency representation as well.

Blind alleys, blinding and blinded aliens : mapping the outer limits of the technical image

Marcia Jane's installation work is situated along a historic line of critical enquiry traceable back to Goethe. her energy field series re-tools for digital use the formal erasures of sturcturalist film, where the relationship between the signifier and the signified are inverted.

Nonnegative blind source separation by sparse component analysis based on determinant measure

The problem of nonnegative blind source separation (NBSS) is addressed in this paper, where both the sources and the mixing matrix are nonnegative. Because many real-world signals are sparse, we deal with NBSS by sparse component analysis. First, a determinant-based sparseness measure, named D-measure, is introduced to gauge the temporal and spatial sparseness of signals. Based on this measure, a new NBSS model is derived, and an iterative sparseness maximization (ISM) approach is proposed to solve this model. In the ISM approach, the NBSS problem can be cast into row-to-row optimizations with respect to the unmixing matrix, and then the quadratic programming (QP) technique is used to optimize each row. Furthermore, we analyze the source identifiability and the computational complexity of the proposed ISM-QP method. The new method requires relatively weak conditions on the sources and the mixing matrix, has high computational efficiency, and is easy to implement. Simulation results demonstrate the effectiveness of our method.

Oral baclofen in children with cerebral palsy : a double-blind cross-over pilot study

Aim: To assess the effectiveness of oral baclofen in reducing spasticity and improving function in children with cerebral palsy. Methods: A double-blind, randomised cross-over pilot study of oral baclofen versus placebo. Assessment tools included the Goal Attainment Scale, Pediatric Evaluation of Disability Inventory, Modified Tardieu Scale and parent questionnaire. Results: Fifteen children with mean age 7.4 years (SD = 2.7 years) and spastic or spastic/dystonic quadriplegia (Gross Motor Function Classification System Level IV or V) were enrolled. Children scored significantly better on the Goal Attainment Scale with baclofen compared with placebo (F(1,13) = 4.5, P = 0.05). There was no significant difference between baclofen and placebo for the Pediatric Evaluation of Disability Inventory or Modified Tardieu Scale. Parent questionnaire results are described. Conclusion: This pilot study demonstrates that oral baclofen has an effect beyond placebo in improving goal-oriented tasks, such as transfers, in children with spastic quadriplegic cerebral palsy.

Novel Z-Domain precoding method for blind separation of spatially correlated signals

In this paper, we address the problem of blind separation of spatially correlated signals, which is encountered in some emerging applications, e.g., distributed wireless sensor networks and wireless surveillance systems. We preprocess the source signals in transmitters prior to transmission. Specifically, the source signals are first filtered by a set of properly designed precoders and then the coded signals are transmitted. On the receiving side, the Z-domain features of the precoders are exploited to separate the coded signals, from which the source signals are recovered. Based on the proposed precoders, a closed-form algorithm is derived to estimate the coded signals and the source signals. Unlike traditional blind source separation approaches, the proposed method does not require the source signals to be uncorrelated, sparse, or nonnegative. Compared with the existing precoder-based approach, the new method uses precoders with much lower order, which reduces the delay in data transmission and is easier to implement in practice.

Projection-pursuit-based method for blind separation of nonnegative sources

This paper presents a projection pursuit (PP) based method for blind separation of nonnegative sources. First, the available observation matrix is mapped to construct a new mixing model, in which the inaccessible source matrix is normalized to be column-sum-to-1. Then, the PP method is proposed to solve this new model, where the mixing matrix is estimated column by column through tracing the projections to the mapped observations in specified directions, which leads to the recovery of the sources. The proposed method is much faster than Chan's method, which has similar assumptions to ours, due to the usage of optimal projection. It is also more advantageous in separating cross-correlated sources than the independence- and uncorrelation-based methods, as it does not employ any statistical information of the sources. Furthermore, the new method does not require the mixing matrix to be nonnegative. Simulation results demonstrate the superior performance of our method.