Active cutaneous warming systems to prevent intraoperative hypothermia: a systematic review

This study analyzed the evidence available in the literature concerning the effectiveness of different active cutaneous warming systems to prevent intraoperative hypothermia. This is a systematic review with primary studies found in the following databases: CINAHL, EMBASE, Cochrane Register of Controlled Trials and Medline. The sample comprised 23 randomized controlled trials. There is evidence in the literature indicating that the circulating water garment system is the most effective in maintaining patient body temperature. These results can support nurses in the decision-making process concerning the implementation of effective measures to maintain normothermia, though the decision of health services concerning which system to choose should also take into account its cost-benefit status given the cost related to the acquisition of such systems.

Effect of parametric uncertainties on the performance of a piezoelectric energy harvesting device

The use of piezoelectric materials for the development of electromechanical devices for the harvesting or scavenging of ambient vibrations has been extensively studied over the last decade. The energy conversion from mechanical (vibratory) to electrical energy is provided by the electromechanical coupling between mechanical strains/stresses and electric charges/voltages in the piezoelectric material. The majority of the studies found in the open literature present a tip-mass cantilever piezoelectric device tuned on the operating frequency. Although recent results show that these devices can be quite effective for harvesting small amounts of electrical energy, little has been published on the robustness of these devices or on the effect of parametric uncertainties on the energy harvested. This work focuses on a cantilever plate with bonded piezoelectric patches and a tip-mass serving as an energy harvesting device. The rectifier and storage electric circuit was replaced by a resistive circuit (R). In addition, an alternative to improve the harvesting performance by adding an inductance in series to the harvesting circuit, thus leading to a resonant circuit (RL), is considered. A coupled finite element model leading to mechanical (displacements) and electrical (charges at electrodes) degrees of freedom is considered. An analysis of the effect of parametric uncertainties of the device on the electric output is performed. Piezoelectric and dielectric constants of the piezoelectric active layers and electric circuit equivalent inductance are considered as stochastic parameters. Mean and confidence intervals of the electric output are evaluated.

Treatment of snoring and sleep apnea syndrome with a removable mandibular advancement device in patients without TMD

INTRODUCTION: Among the sleep disorders reported by the American Academy of Sleep, the most common is obstructive sleep apnea-hypopnea syndrome (OSAHS), which is caused by difficulties in air passage and complete interruption of air flow in the airway. This syndrome is associated with increased morbidity and mortality in apneic individuals. OBJECTIVE: It was the objective of this paper to evaluate a removable mandibular advancement device as it provides a noninvasive, straightforward treatment readily accepted by patients. METHODS: In this study, 15 patients without temporomandibular disorders (TMD) and with excessive daytime sleepiness or snoring were evaluated. Data were collected by means of: Polysomnography before and after placement of an intraoral appliance, analysis of TMD signs and symptoms using a patient history questionnaire, muscle and TMJ palpation. RESULTS: After treatment, the statistical analysis (t-test, and the "before and after" test) showed a mean reduction of 77.6% (p=0.001) in the apnea-hypopnea index, an increase in lowest oxyhemoglobin saturation (p=0.05), decrease in desaturation (p=0.05), decrease in micro-awakenings or EEG arousals (p=0.05) and highly significant improvement in daytime sleepiness (p=0.005), measured by the Epworth Sleepiness Scale. No TMD appeared during the monitoring period. CONCLUSION: The oral device developed in this study was considered effective for mild to moderate OSAHS.

Development of heat sink device by using topology optimization

Small scale fluid flow systems have been studied for various applications, such as chemical reagent dosages and cooling devices of compact electronic components. This work proposes to present the complete cycle development of an optimized heat sink designed by using Topology Optimization Method (TOM) for best performance, including minimization of pressure drop in fluid flow and maximization of heat dissipation effects, aiming small scale applications. The TOM is applied to a domain, to obtain an optimized channel topology, according to a given multi-objective function that combines pressure drop minimization and heat transfer maximization. Stokes flow hypothesis is adopted. Moreover, both conduction and forced convection effects are included in the steady-state heat transfer model. The topology optimization procedure combines the Finite Element Method (to carry out the physical analysis) with Sequential Linear Programming (as the optimization algorithm). Two-dimensional topology optimization results of channel layouts obtained for a heat sink design are presented as example to illustrate the design methodology. 3D computational simulations and prototype manufacturing have been carried out to validate the proposed design methodology.

A system for classification of time-series data from industrial non-destructive device

This work proposes a system for classification of industrial steel pieces by means of magnetic nondestructive device. The proposed classification system presents two main stages, online system stage and off-line system stage. In online stage, the system classifies inputs and saves misclassification information in order to perform posterior analyses. In the off-line optimization stage, the topology of a Probabilistic Neural Network is optimized by a Feature Selection algorithm combined with the Probabilistic Neural Network to increase the classification rate. The proposed Feature Selection algorithm searches for the signal spectrogram by combining three basic elements: a Sequential Forward Selection algorithm, a Feature Cluster Grow algorithm with classification rate gradient analysis and a Sequential Backward Selection. Also, a trash-data recycling algorithm is proposed to obtain the optimal feedback samples selected from the misclassified ones.