Interference of the direct and ground-reflected waves in the atmosphere with volumetric scatteringa).

The interference of the direct and ground-reflected sound waves is significantly affected by volumetric scattering in the atmosphere, such as scattering by turbulence and forest. In the present article, the existing theory describing this interference is generalized to three somewhat independent but equally important cases. First, the attenuation of the direct and ground-reflected waves caused by backscattering is addressed. Second, the existing theory is extended for statistically quasi-homogeneous turbulence in which the variances and length scales of the temperature and wind velocity fluctuations depend on the height above the ground. Third, the existing theory, which was previously formulated only for near-horizontal sound propagation, is generalized to slanted sound propagation as pertinent to elevated sound sources. Numerical results for slanted propagation demonstrate that atmospheric turbulence can significantly increase the sound pressure level at the interference minima. The extended theory of the interference of the direct and ground-reflected waves in the atmosphere with volumetric scattering is important for practical applications, such as auralization of flying aircraft and sound propagation in a forest, and can be adapted to radio wave propagation.

Urban noise distributions and the influence of geometric spreading on skewness.

Statistical distributions of urban noise levels are influenced by many complex phenomena, including spatial and temporal variations in the source level, multisource mixtures, propagation losses, and random fading from multipath reflections. This article provides a broad perspective on the varying impacts of these phenomena. Distributions incorporating random fading and averaging (e.g., gamma and noncentral Erlang) tend to be negatively skewed on logarithmic (decibel) axes but can be positively skewed if the fading process is strongly modulated by source power variations (e.g., compound gamma). In contrast, distributions incorporating randomly positioned sources and explicit geometric spreading [e.g., exponentially modified Gaussian (EMG)] tend to be positively skewed with exponential tails on logarithmic axes. To evaluate the suitability of the various distributions, one-third octave band sound-level data were measured at 37 locations in the North End of Boston, MA. Based on the Kullback-Leibler divergence as calculated across all of the locations and frequencies, the EMG provides the most consistently good agreement with the data, which were generally positively skewed. The compound gamma also fits the data well and even outperforms the EMG for the small minority of cases exhibiting negative skew. The lognormal provides a suitable fit in cases in which particular non-traffic noise sources dominate.

Quantifying signal dispersion in a hybrid ice core melting system.

We describe a microcontroller-based ice core melting and data logging system allowing simultaneous depth coregistration of a continuous flow analysis (CFA) system (for microparticle and conductivity measurement) and a discrete sample analysis system (for geochemistry and microparticles), both supplied from the same melted ice core section. This hybrid melting system employs an ice parcel tracking algorithm which calculates real-time sample transport through all portions of the meltwater handling system, enabling accurate (1 mm) depth coregistration of all measurements. Signal dispersion is analyzed using residence time theory, experimental results of tracer injection tests and antiparallel melting of replicate cores to rigorously quantify the signal dispersion in our system. Our dispersion-limited resolution is 1.0 cm in ice and ~2 cm in firn. We experimentally observe the peak lead phenomenon, where signal dispersion causes the measured CFA peak associated with a given event to be depth assigned ~1 cm shallower than the true event depth. Dispersion effects on resolution and signal depth assignment are discussed in detail. Our results have implications for comparisons of chemistry and physical properties data recorded using multiple instruments and for deconvolution methods of enhancing CFA depth resolution.

Human preferences for symmetry: subjective experience, cognitive conflict and cortical brain activity.

This study examines the links between human perceptions, cognitive biases and neural processing of symmetrical stimuli. While preferences for symmetry have largely been examined in the context of disorders such as obsessive-compulsive disorder and autism spectrum disorders, we examine various these phenomena in non-clinical subjects and suggest that such preferences are distributed throughout the typical population as part of our cognitive and neural architecture. In Experiment 1, 82 young adults reported on the frequency of their obsessive-compulsive spectrum behaviors. Subjects also performed an emotional Stroop or variant of an Implicit Association Task (the OC-CIT) developed to assess cognitive biases for symmetry. Data not only reveal that subjects evidence a cognitive conflict when asked to match images of positive affect with asymmetrical stimuli, and disgust with symmetry, but also that their slowed reaction times when asked to do so were predicted by reports of OC behavior, particularly checking behavior. In Experiment 2, 26 participants were administered an oddball Event-Related Potential task specifically designed to assess sensitivity to symmetry as well as the OC-CIT. These data revealed that reaction times on the OC-CIT were strongly predicted by frontal electrode sites indicating faster processing of an asymmetrical stimulus (unparallel lines) relative to a symmetrical stimulus (parallel lines). The results point to an overall cognitive bias linking disgust with asymmetry and suggest that such cognitive biases are reflected in neural responses to symmetrical/asymmetrical stimuli.