Modified constraint-induced movement therapy and modified forced-use therapy for stroke patients are both effective to promote balance and gait improvements

Background: Previous studies show that chronic hemiparetic patients after stroke, presents inabilities to perform movements in paretic hemibody. This inability is induced by positive reinforcement of unsuccessful attempts, a concept called learned non-use. Forced use therapy (FUT) and constraint induced movement therapy (CIMT) were developed with the goal of reversing the learned non-use. These approaches have been proposed for the rehabilitation of the paretic upper limb (PUL). It is unknown what would be the possible effects of these approaches in the rehabilitation of gait and balance. Objectives: To evaluate the effect of Modified FUT (mFUT) and Modified CIMT (mCIMT) on the gait and balance during four weeks of treatment and 3 months follow-up. Methods: This study included thirty-seven hemiparetic post-stroke subjects that were randomly allocated into two groups based on the treatment protocol. The non-paretic UL was immobilized for a period of 23 hours per day, five days a week. Participants were evaluated at Baseline, 1st, 2nd, 3rd and 4th weeks, and three months after randomization. For the evaluation we used: The Stroke Impact Scale (SIS), Berg Balance Scale (BBS) and Fugl-Meyer Motor Assessment (FM). Gait was analyzed by the 10-meter walk test (T10) and Timed Up & Go test (TUG). Results: Both groups revealed a better health status (SIS), better balance, better use of lower limb (BBS and FM) and greater speed in gait (T10 and TUG), during the weeks of treatment and months of follow-up, compared to the baseline. Conclusion: The results show mFUT and mCIMT are effective in the rehabilitation of balance and gait. Trial Registration ACTRN12611000411943.

Trauma and countertransference: development and validity of the Assessment of Countertransference Scale (ACS)

Objectives: The aim of the present study was to investigate the construct validity of the Assessment of Countertransference Scale (ACS) in the context of the trauma care, through the identification of the underlying latent constructs of the measured items and their homogeneity. Methods: ACS assesses 23 feelings of CT in three factors: closeness, rejection and indifference. ACS was applied to 50 residents in psychiatry after the first appointment with 131 victims of trauma consecutively selected during 4 years. ACS was analyzed by exploratory (EFA) and confirmatory (CFA) factor analysis, internal consistence and convergent-discriminant validity. Results: In spite of the fact that closeness items obtained the highest scores, the EFA showed that the factor rejection (24% of variance, alpha = 0.88) presented a more consistent intercorrelation of the items, followed by closeness (15% of variance, alpha = 0.82) and, a distinct factor, sadness (9% of variance, alpha = 0.72). Thus, a modified version was proposed. In the comparison between the original and the proposed version, CFA detected better goodness-of-fit indexes for the proposed version (GFI = 0.797, TLI = 0.867, CFI = 0.885 vs. GFI = 0.824, TLI = 0.904, CFI = 0.918). Conclusions: ACS is a promising instrument for assessing CT feelings, making it valid to access during the care of trauma victims.

A modified Primal-Dual Logarithmic-Barrier Method for solving the Optimal Power Flow problem with discrete and continuous control variables

The aim of solving the Optimal Power Flow problem is to determine the optimal state of an electric power transmission system, that is, the voltage magnitude and phase angles and the tap ratios of the transformers that optimize the performance of a given system, while satisfying its physical and operating constraints. The Optimal Power Flow problem is modeled as a large-scale mixed-discrete nonlinear programming problem. This paper proposes a method for handling the discrete variables of the Optimal Power Flow problem. A penalty function is presented. Due to the inclusion of the penalty function into the objective function, a sequence of nonlinear programming problems with only continuous variables is obtained and the solutions of these problems converge to a solution of the mixed problem. The obtained nonlinear programming problems are solved by a Primal-Dual Logarithmic-Barrier Method. Numerical tests using the IEEE 14, 30, 118 and 300-Bus test systems indicate that the method is efficient. (C) 2012 Elsevier B.V. All rights reserved.