No abstract

Fast frequency modulations (FM) are an essential part of species-specific auditory signals in animals as well as in human speech. Major parameters characterizing non-periodic frequency modulations are the direction of frequency change in the FM sweep (upward/downward) and the sweep speed, i.e., the speed of frequency change. While it is well established that both parameters are represented in the mammalian central auditory pathway, their importance at the perceptual level in animals is unclear. We determined the ability of rats to discriminate between upward and downward modulated FM-tones as a function of sweep speed in a two-alternative-forced-choice-paradigm. Directional discrimination in logarithmic FM-sweeps was reduced with increasing sweep speed between 20 and 1,000 octaves/s following a psychometric function. Average threshold sweep speed for FM directional discrimination was 96 octaves/s. This upper limit of perceptual FM discrimination fits well the upper limit of preferred sweep speeds in auditory neurons and the upper limit of neuronal direction selectivity in the rat auditory cortex and midbrain, as it is found in the literature. Influences of additional stimulus parameters on FM discrimination were determined using an adaptive testing-procedure for efficient threshold estimation based on a maximum likelihood approach. Directional discrimination improved with extended FM sweep range between two and five octaves. Discrimination performance declined with increasing lower frequency boundary of FM sweeps, showing an especially strong deterioration when the boundary was raised from 2 to 4 kHz. This deterioration corresponds to a frequency-dependent decline in direction selectivity of FM-encoding neurons in the rat auditory cortex, as described in the literature. Taken together, by investigating directional discrimination of FM sweeps in the rat we found characteristics at the perceptual level that can be related to several aspects of FM encoding in the central auditory pathway.

Monitoring water quality in sewers is challenging, particularly because state-of-the-art technologies require contact with the raw wastewater. The presence of fat, oil, grease and solids makes automated grab sampling difficult and causes sensor fouling. To overcome these limitations, non-contact methods based on light reflectance, such as hyperspectral imaging (HSI), are gaining attention. However, HSI has never been tested for raw wastewater. To assess its accuracy for measuring pollution, we developed a laboratory setup and performed targeted experiments with a combination of raw and diluted wastewater, as well as synthetic turbidity stock solutions. We measured seven pollution variables: chemical oxygen demand, turbidity, dissolved organic compounds, ammonium, total nitrogen, phosphate, and sulphates. We used automated pixel selection and partial least squares regression to retrieve pollution information from the hyperspectral images. Our results, based on 144 samples, suggest that HSI can estimate pollution levels with a precision in the range of state-of-the-art absorbance spectroscopy methods. Additionally, we found that the combination of pixel and wavelength selection, enabled by the hyperspectral data structure, significantly influences the performance of partial least square modelling. Overall, our findings indicate that HSI is a promising technology for non-contact monitoring of water quality in raw wastewater.