Rehabilitative management of swallowing and oral-motor movements in patients with tetanus of a public service in Brazil

When looking at developing countries, the prolonged intensive medical and nursing care required by many patients places extra demands on an already stretched healthcare budget. The purpose of this study was to verify the effectiveness of a systematic rehabilitative program for swallowing and oral-motor movements in intensive care unit patients with the diagnosis of tetanus. Forty-five patients who were clinically diagnosed with tetanus were included in the study. Participants were divided in two groups: Cl - consisted of 18 tetanus patients who were consecutively admitted to the infectious disease ICU from January 2002 to December 2005, prior to the existence of a systematic swallowing and oral-motor intervention: GII - consisted of 27 tetanus patients who were consecutively admitted to the infectious disease ICU from January 2006 to December 2009 and were submitted to a specific rehabilitative management of swallowing and of the oral-motor movements. Results indicate that the proposed rehabilitative program reduced by approximately 50% the time patients remained in the ICU. The significant improvement observed in patients with tetanus who were submitted to the rehabilitative program for swallowing and oral-motor movements occurred in conjunction with a reduction in the amount of time necessary to reintroduce oral feeding, to decannulate and to remove the feeding tubes. In conclusion, swallowing/muscle exercise, in patients with severe/very severe tetanus, seem to promote the remission of muscle tension and seem to maximize functional swallowing. (C) 2012 Elsevier B.V. All rights reserved.

Multi-objective evolutionary algorithm for single and multiple fault service restoration in large-scale distribution systems

Network reconfiguration for service restoration (SR) in distribution systems is a complex optimization problem. For large-scale distribution systems, it is computationally hard to find adequate SR plans in real time since the problem is combinatorial and non-linear, involving several constraints and objectives. Two Multi-Objective Evolutionary Algorithms that use Node-Depth Encoding (NDE) have proved able to efficiently generate adequate SR plans for large distribution systems: (i) one of them is the hybridization of the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) with NDE, named NSGA-N; (ii) the other is a Multi-Objective Evolutionary Algorithm based on subpopulation tables that uses NDE, named MEAN. Further challenges are faced now, i.e. the design of SR plans for larger systems as good as those for relatively smaller ones and for multiple faults as good as those for one fault (single fault). In order to tackle both challenges, this paper proposes a method that results from the combination of NSGA-N, MEAN and a new heuristic. Such a heuristic focuses on the application of NDE operators to alarming network zones according to technical constraints. The method generates similar quality SR plans in distribution systems of significantly different sizes (from 3860 to 30,880 buses). Moreover, the number of switching operations required to implement the SR plans generated by the proposed method increases in a moderate way with the number of faults.