Estimating phonation threshold pressure

Phonation threshold pressure (PTP) is the minimum subglottal pressure required to initiate vocal fold oscillation. Although potentially useful clinically, PTP is difficult to estimate noninvasively because of limitations to vocal motor control near the threshold of soft phonation. Previous investigators observed, for example, that trained subjects were unable to produce flat, consistent oral pressure peaks during/pae/syllable strings when they attempted to phonate as softly as possible (Verdolini-Marston, Titze, & Druker, 1990). The present study aimed to determine if nasal airflow or vowel context affected phonation threshold pressure as estimated from oral pressure (Smitheran & Hixon, 1981) in 5 untrained female speakers with normal velopharyngeal and voice function. Nasal airflow during /p/occlusion was observed for 3 of 5 participants when they attempted to phonate near threshold pressure. When the nose was occluded, nasal airflow was reduced or eliminated during /p/;however, individuals then evidenced compensatory changes in glottal adduction and/or respiratory effort that may be expected to alter PTP estimates. Results demonstrate the importance of monitoring nasal flow (or the flow zero point in undivided masks) when obtaining PTP measurements noninvasively. Results also highlight the need to pursue improved methods for noninvasive estimation of PTP.     

Pegylated peptides. V. Carboxy-terminal PEGylated analogs of growth hormone-releasing factor (GRF) display enhanced duration of biological activity in vivo

In the present study, human growth hormone-releasing factor (hGRF) and analogs were successfully pegylated at the carboxy-terminus using a novel solid- and solution-phase strategy. Following synthesis, these pegylated hGRF analogs were evaluated for in vitro and in vivo biological activity. Specifically, hGRF (1-29)-NH2, [Ala15]-hGRF (1-29)-NH2, [desNH2Tyr1, D-Ala2, Ala15]-hGRF(1-29)-NH2 and [His1, Val2, Gln8, Ala15, Leu27]-hGRF(1-32)-OH were each C-terminally extended using a Gly-Gly-Cys-NH2 spacer (previously demonstrated not to alter intrinsic biological activity), and then monopegylated via coupling to an activated dithiopyridyl-PEG reagent. PEG moieties of 750, 2000, 5000 or 10,000 molecular weight (MW) were examined to determine the effect of polymer weight on activity. Initial biological evaluations in vitro revealed that all C-terminally pegylated hGRF analogs retained high growth hormone (GH)-releasing potencies, regardless of the MW of PEG polymer employed. Two of these pegylated hGRF analogs, [desNH2Tyr1, D-Ala2, Ala15]-hGRF (1-29)-Gly-Gly-Cys(NH2)-S-Nle-PEG5000 and [His1, Val2, Gln8, Ala15, Leu27]-hGRF(1-32)-Gly-Cys(NH2)-S-Nle-PEG5000, were subsequently evaluated in both pig and mouse models and found to be highly potent (in vivo potency range = 12-55-fold that of native hGRF). Relative to their non-pegylated counterparts, these two pegylated hGRF analogs exhibited enhanced duration of activity.     

Thermal-lens and photo-acoustic methods for the determination of SiC thermal properties

In this paper we report the use of photothermal techniques such as Thermal lens (TL) spectrometry, Photoacoustic and heat capacity, ρc_p, to determine the thermo-optical parameters, such as thermal conductivity (K), thermal diffusivity (D), specific heat (c_p) and the optical path dependence with temperature (ds/dT), of an undoped polycrystalline 3C-SiC. To our knowledge, this is the first time that Thermal lens technique is used for wide band-gap systems. Results obtained for the polycrystalline sample with TL technique indicates that ds/dT is negative at room temperature. Moreover, the obtained values of thermal diffusivity and thermal conductivity are in good agreement with that found in the literature, indicating that the phototermal techniques can be used to obtain the referred parameters in circumstances where other techniques cannot be used, for example, in harsh environments.     

Learning user preferences of route choice behaviour for adaptive route guidance

As the use of navigation systems becomes more widespread, the demand for advanced functions of navigation systems also increases. In the light of user satisfaction, personalisation of route guidance by incorporating user preferences is one of the most desired features. A user model applied to personalised route guidance is presented. The user model adaptively updates route selection rules when it discovers the predicted choice differs from the actual choice of the driver. This study employs a decision tree learning algorithm, the C4.5 algorithm, which has advantages over other data mining methods in terms of its comprehensible model structure. Simulation experiments with a real-world network were conducted to analyse the applicability of the model to adaptive route guidance and the accuracy of its prediction