Zobrazení zdroje stránky Malmbergberg3613

Hearing a sound produces vibrations of the ossicles in the middle ear, which can be measured in the micrometer to nanometer range. Destruction of middle ear structures results most commonly from chronic inflammatory diseases. In these cases, passive and active middle ear implants are used for reconstruction of the ossicular chain. The positioning of the implants depends primarily on the surgeon's experience. So far, no objective assessment has been conducted to affirm if the chosen positioning is the best in each specific case. We have established a new method, allowing us to measure the middle ear transfer function (METF) intraoperatively. Using the new method, a magnet is placed on the umbo of the malleus handle and is stimulated by a coil positioned underneath the head. The resulting vibration is measured on the stapes footplate using Laser Doppler vibrometry (LDV). Acoustic and electromagnetic excitation show comparable METF in lower frequencies, which differ up to 10 dB in frequencies over 1 kHz. The position of the coil does not play a relevant part in the METF, whereas the location of the magnet on the tympanic membrane highly impacts the METF. This technique demonstrates reproducible results. Electromagnetic excitation is comparable to sound excitation and is suited for measuring the METF. A stable positioning of the magnet on the umbo is essential in order to acquire valid data.Spatial variation of the levels of polycyclic aromatic hydrocarbons (PAHs) was evaluated within an urban-industrial district where the main anthropogenic pressures are a 15 MW biomass power plant (BPP) and road traffic. The use of a high-density lichen transplant network and wind quantitative relationships made it possible to perform a hierarchical analysis of contamination. Combined uni-bi and multivariate statistical analyses of the resulting databases revealed a dual pattern. In its surroundings (local scale), the BPP affected the bioaccumulation of fluoranthene, pyrene and total PAHs, although a confounding effect of traffic (mostly petrol/gasoline engines) was evident. Spatial variation of the rate of diesel vehicles showed a significant association with that of acenaphthylene, acenaphthene, fluorene, anthracene and naphthalene. The series of high-speed wind values suggests that wind promotes diffusion rather than dispersion of the monitored PAHs. At the whole study area scale, the BPP was a source of acenaphthylene and acenaphthene, while diesel vehicles were a source of acenaphthylene. PAHs contamination strongly promotes oxidative stress (a threefold increase vs pre-exposure levels) in lichen transplants, suggesting a marked polluting effect of anthropogenic sources especially at the expense of the mycobiont. The proposed monitoring approach could improve the apportionment of the different contributions of point and linear anthropogenic sources of PAHs, mitigating the reciprocal biases affecting their spatial patterns.Numerous statistical models have established the relationship between ambient fine particulate matter (PM2.5, with an aerodynamic diameter of less than 2.5 μm) and satellite aerosol optical depth (AOD) along with other meteorological/land-related covariates. However, all the models assumed that all covariates affect the PM2.5 concentration at the same scale, and none could provide a posterior uncertainty analysis at each regression point. Therefore, a multiscale geographically and temporally weighted regression (MGTWR) model was proposed by specifying a unique bandwidth for each covariate. [https://www.selleckchem.com/products/dasa-58.html buy DASA-58] However, the lack of a method for predicting values at unsampled points in the MGTWR model greatly restricts its corresponding application. Thus, this study developed a method for inferring unsampled points and used the posterior uncertainty assessment value to improve the model accuracy. With the aid of the high-resolution satellite multi-angle implementation of atmospheric correction (MAIAC) AOD product, daily PM2.5 concentrations with a 1 km × 1 km resolution were generated over the Beijing-Tianjin-Hebei region between 2013 and 2019. The coefficient of determination (R2) and root mean square error (RMSE) of the fitted MGTWR results vary from 0.90 to 0.94 and from 10.66 to 25.11 μg/m3, respectively. The sample-based and site-based cross-validation R2 and RMSE vary from 0.81 to 0.89 and from 14.40 to 34.43 μg/m3 respectively, demonstrating the effectiveness of the proposed inference method at unsampled points. With the uncertainty constraint, the sample-based and site-based validated MGTWR R2 results for all years are further improved by approximately 0.02-0.04, demonstrating the effectiveness of the posterior uncertainty assessment constraint method. These results suggest that the inference method proposed in this study is promising to overcome the defects of the MGTWR model in inferring the prediction values at unsampled points and could consequently enhance the wide applications of MGTWR modeling.Potato (Solanum tuberosum L.) production in irrigated coarse-textured soils requires intensive nitrogen (N) fertilization which may increase reactive N losses. Biological soil additives including N-fixing microbes (NFM) have been promoted as a means to increase crop N use efficiency, though few field studies have evaluated their effects, and none have examined the combined use of NFM with microbial inhibitors. A 2-year study (2018-19) in an irrigated loamy sand quantified the effects of the urease inhibitor NBPT, the nitrification inhibitor DMPSA, NFM, and the additive combinations DMPSA + NBPT and DMPSA + NFM on potato performance and growing season nitrous oxide (N2O) emissions and nitrate (NO3-) leaching. All treatments, except a zero-N control, received diammonium phosphate at 45 kg N ha-1 and split applied urea at 280 kg N ha-1. Compared with urea alone, DMPSA + NBPT reduced NO3- leaching and N2O emissions by 25% and 62%, respectively, and increased crop N uptake by 19% in one year, although none of the additive treatments increased tuber yields. The DMPSA and DMPSA + NBPT treatments had greater soil ammonium concentration, and all DMPSA-containing treatments consistently reduced N2O emissions, compared to urea-only. Use of NBPT by itself reduced NO3- leaching by 21% across growing seasons and N2O emissions by 37% in 2018 relative to urea-only. In contrast to the inhibitors, NFM by itself increased N2O by 23% in 2019; however, co-applying DMPSA with NFM reduced N2O emissions by ≥ 50% compared to urea alone. These results demonstrate that DMPSA can mitigate N2O emissions in potato production systems and that DMPSA + NBPT can reduce both N2O and NO3- losses and increase the N supply for crop uptake. This is the first study to show that combining a nitrification inhibitor with NFM can result in decreased N2O emissions in contrast to unintended increases in N2O emissions that can occur when NFM is applied by itself.