Development of an algorithm for the diagnosis of otitis media

Background: The relative importance of signs and symptoms in the diagnosis of otitis media has not been adequately evaluated. This has led to a large degree of variation in the criteria used to diagnose otitis media, which has resulted in inconsistencies in clinical care and discrepant research findings. Methods: A group of experienced otoscopists examined children presenting for primary care. We investigated the signs and symptoms that these otoscopists used to distinguish acute otitis media (AOM), otitis media with effusion (OME), and no effusion. We used recursive partitioning to develop a diagnostic algorithm. To assess the algorithm, we validated it in an independent dataset. Results: Bulging of the tympanic membrane (TM) was the main finding that otoscopists used to discriminate AOM from OME; information regarding the presence or absence of other signs and symptoms added little to the diagnostic process. Overall, 92% of children with AOM had a bulging TM compared with 0% of children with OME. Opacification and/or an air-fluid level was the main finding that the otoscopists used to discriminate OME from no effusion; 97% of children diagnosed with OME had an opaque TM compared with 5% of children diagnosed with no effusion. An algorithm that used bulging and opacification of the TM correctly classified 99% of ears in an independent dataset. Conclusions: Bulging of the TM was the finding that best discriminated AOM from OME. The algorithm developed here may prove to be useful in clinical care, research, and education concerning otitis media. Copyright © 2012 by Academic Pediatric Association

Wireless battery charger for ev with circular or planar coils: comparison

This paper presents the experimental results obtained in the wireless energy transfer system prototype based on circular or planar coils. With these experimental results we can choose the tuning settings to improve the power transmission efficiency in wireless energy transfer systems. In wireless energy transfer for electric vehicle batteries charging, the coil shape and the range between the coils are the most important issues of those systems

A Glucose Fuel Cell for Implantable Brain–Machine Interfaces

We have developed an implantable fuel cell that generates power through glucose oxidation, producing steady-state power and up to peak power. The fuel cell is manufactured using a novel approach, employing semiconductor fabrication techniques, and is therefore well suited for manufacture together with integrated circuits on a single silicon wafer. Thus, it can help enable implantable microelectronic systems with long-lifetime power sources that harvest energy from their surrounds. The fuel reactions are mediated by robust, solid state catalysts. Glucose is oxidized at the nanostructured surface of an activated platinum anode. Oxygen is reduced to water at the surface of a self-assembled network of single-walled carbon nanotubes, embedded in a Nafion film that forms the cathode and is exposed to the biological environment. The catalytic electrodes are separated by a Nafion membrane. The availability of fuel cell reactants, oxygen and glucose, only as a mixture in the physiologic environment, has traditionally posed a design challenge: Net current production requires oxidation and reduction to occur separately and selectively at the anode and cathode, respectively, to prevent electrochemical short circuits. Our fuel cell is configured in a half-open geometry that shields the anode while exposing the cathode, resulting in an oxygen gradient that strongly favors oxygen reduction at the cathode. Glucose reaches the shielded anode by diffusing through the nanotube mesh, which does not catalyze glucose oxidation, and the Nafion layers, which are permeable to small neutral and cationic species. We demonstrate computationally that the natural recirculation of cerebrospinal fluid around the human brain theoretically permits glucose energy harvesting at a rate on the order of at least 1 mW with no adverse physiologic effects. Low-power brain–machine interfaces can thus potentially benefit from having their implanted units powered or recharged by glucose fuel cells