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OBJECTIVE: The frequency specific maximum output (MO) of active middle ear implants is the most crucial parameter for speech intelligibility. We determined individual MO from clinical routine data in round window (RW) coupling of the Vibrant Soundbridge (VSB). DESIGN: Monocentric, retrospective analysis. STUDY SAMPLE: 68 ears implanted with the VSB at the RW were analysed. Using bone conduction and direct threshold, MO was determined for combinations of implants (VORP502, VORP503) and processors (Samba, Amadé). Coupling modes were: (A) without coupler (N = 28), (B) spherical coupler (N = 19), (C) soft coupler (N = 10) or (D) custom-made "Hannover coupler" (N = 11). RESULTS: The MO frequency dependence was similar for coupling types (A-D) with a maximum at 1.5 kHz. No differences between groups were observed, although the average MO of the soft coupler was 10 dB lower. The average MO (0.5, 1.0, 2.0, 4.0 kHz) was (A) 77.6 ± 15.0 dB HL, (B) 81.0 ± 11.1 dB HL, (C) 67.6 ± 17.9 dB HL (C), and (D) 79.6 ± 11.7 dB HL (D). CONCLUSION: The individual MO can be determined from patients' clinical data. It permits in-depth analyses of patient outcomes and definition of evidence-based indication and decision criteria.

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Aiming to overcome both the structural and commercial limitations of flexible thermoelectric power generators, an efficient room-temperature aqueous selenization reaction that can be completed in air within less than 1 min, to directly fabricate thin ß-Ag2 Se films consisting of perfectly crystalline and large columnar grains with both in-plane randomness and out-of-plane [201] preferred orientation, is designed. A high power factor (PF) of 2590 ± 414 µW m-1 K-2 and a figure-of-merit (zT) of 1.2 ± 0.42 are obtained from a sample with a thickness of ≈1 µm. The maximum output power density of the best 4-leg thermoelectric generator sample reach 27.6 ± 1.95 and 124 ± 8.78 W m-2 at room temperature with 30 and 60 K temperature differences, respectively, which may be useful in future flexible thermoelectric devices.

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This paper theoretically presented the temperature effects on the 63Ni-Si betavoltaic microbattery irradiated by a source with different thicknesses and activity densities at a temperature range 170-340K. Temperature dependences of the monolayer and interbedded 63Ni-Si betavoltaics at 213.15-333.15K were tested with respect to calculations. Results showed that the higher the thickness, activity density, and average energy of the source, the lower is the betavoltaic performance responds to temperature. With the increase in temperature, the Voc and Pmax of the upper, lower, and interbedded betavoltaics decreased linearly at low temperatures and decreased exponentially at high temperatures in the experiment. As predicted, the measured Voc and Pmax sensitivities of the lower betavoltaic with 4.90mCi/cm2 63Ni, -2.230mV/K and -1.132%, respectively, were lower than those with 1.96mCi/cm2 63Ni, -2.490mV/K and -1.348%, respectively. Compared with the calculated results, the prepared betavoltaics had lower Voc sensitivity and higher Pmax sensitivity. In addition, the measured Voc sensitivity of the interbedded betavoltaic in series is equal to the sum of those of the upper and lower ones as predicted. Moreover, the measured Pmax sensitivity of the interbedded betavoltaic is equal to the average of those of the two monolayers.

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BACKGROUND: Various different hearing systems are available for device-supported hearing rehabilitation of patients with mixed hearing loss. Using the recently introduced objective comparison criterion "maximum output" (i.e., the maximum output level of a hearing device), the indications for different hearing devices can be compared. OBJECTIVE: This article reviews important terms such as gain, dynamic range, and maximum output level-all of which are relevant for the selection of a hearing device. The experimental part of this study compares all currently available hearing devices and determines the range of their indication with respect to the maximum bone-conduction hearing threshold. MATERIALS AND METHODS: The maximum frequency-specific output levels reported in the literature for the Baha Cordelle 2, the Sophono Alpha 2, and the Bonebridge (measured at the skull simulator), as well as those of the Codacs and the Soundbridge (in-vivo measurements) are compared to the maximum output levels given in the datasheets of the BP110 Power, the Baha Cordelle 2, the Bonebridge, the Codacs, the Ponto Pro Power, and the Sophono Alpha 2. Using appropriate correction factors, the maximum dynamic range and thus the maximum indication based on the bone-conduction threshold was determined. RESULTS: In patients with mild sensorineural hearing loss, passive transcutaneous hearing or Bonebridge implants can achieve good audiological results. In the transition region to moderate hearing loss, percutaneous devices are applicable. Combined hearing loss with more pronounced sensorineural hearing loss is best treated with a Soundbridge or Codacs implant. In the latter case, the cochlear potential for speech recognition has to be explored and, where appropriate, cochlear implants considered as an alternative.

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Primary and Secondary Polycythemia are diseases of the bone marrow that affect the blood's composition and prohibit patients from becoming blood donors. Since these diseases may become fatal, their early diagnosis is important. In this paper, a classification system for the diagnosis of Primary and Secondary Polycythemia is proposed. The proposed system classifies input data into three classes; Healthy, Primary Polycythemic (PP) and Secondary Polycythemic (SP) and is implemented using two separate binary classification levels. The first level performs the Healthy/non-Healthy classification and the second level the PP/SP classification. To this end, a novel wrapper feature selection algorithm, called the LM-FM algorithm, is presented in order to maximize the classifier's performance. The algorithm is comprised of two stages that are applied sequentially: the Local Maximization (LM) stage and the Floating Maximization (FM) stage. The LM stage finds the best possible subset of a fixed predefined size, which is then used as an input for the next stage. The FM stage uses a floating size technique to search for an even better solution by varying the initially provided subset size. Then, the Support Vector Machine (SVM) classifier is used for the discrimination of the data at each classification level. The proposed classification system is compared with various well-established feature selection techniques such as the Sequential Floating Forward Selection (SFFS) and the Maximum Output Information (MOI) wrapper schemes, and with standalone classification techniques such as the Multilayer Perceptron (MLP) and SVM classifier. The proposed LM-FM feature selection algorithm combined with the SVM classifier increases the overall performance of the classification system, scoring up to 98.9% overall accuracy at the first classification level and up to 96.6% at the second classification level. Moreover, it provides excellent robustness regardless of the size of the input feature subset used.

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