Ray-trace modeling of acoustic Green's function based on the semiclassical (eikonal) approximation.

The Green's function (GF) for the scalar wave equation is numerically constructed by an advanced geometric ray-tracing method based on the eikonal approximation related to the semiclassical propagator. The underlying theory is first briefly introduced, and then it is applied to acoustics and implemented in a ray-tracing-type numerical simulation. The so constructed numerical method is systematically used to calculate the sound field in a rectangular (cuboid) room, yielding also the acoustic modes of the room. The simulated GF is rigorously compared to its analytic approximation. Good agreement is found, which proves the devised numerical approach potentially useful also for low frequency acoustic modeling, which is in practice not covered by geometrical methods.

An objective measure for the sensitivity of room impulse response and its link to a diffuse sound field.

This study is relevant to acoustic measurements in reverberation rooms such as measurements of sound transmission, sound absorption, and sound power levels of noise sources. The study presents a quantitative measure for the diffuseness in a room, which is first introduced theoretically and subsequently examined experimentally. The sensitivity of a room due to changes in the initial conditions is quantified by measuring a pair of impulse responses in a room differing only in the sound source position. Such changes are linked to mixing and the diffuse sound field. The measure is based on the maximum of the absolute value of the cross-correlation between the time windowed sections of the two impulse responses. By integrating this quantity normalized by the energy of the impulse response of the room, a single number rating is obtained. Results based on three sets of experiments indicate that the diffusers and absorbers in the room influence the proposed sensitivity measures systematically.

What type of social media posts about sustainable construction is better for audience engagement?

Background: In an effort to move to a sustainable society, new concepts and findings related to sustainable construction are being developed. With ambition to transfer newly developed knowledge to society, various communication paths are being used. In this study we investigated what kind of messages shared on institutional social media channels (Facebook, Twitter (now renamed to X), and LinkedIn) about sustainable construction create more audience engagement. Methods: The study consisted of two phases of weekly social media posts. In each phase, 15 posts were published on the same day and time, while engagement was monitored. Three different types of posts were created, that were sequential cycling each week. Type 1 was written informative content related to research activities; type 2 was image content related to the research activities and equipment, with a short text caption of the image; and type 3 was image content with people - scientists working on research activities with a short text caption of the image. Results: Poisson regression analysis revealed that type 3 posts result in the most audience engagement on LinkedIn, suggesting that using images of people in combination with short text captions is the most effective way to engage social media audiences. These findings can help organizations to use social media to promote sustainable construction and other sustainability-related research. The engagement was lower on Facebook and Twitter (X). Conclusions: As the science is aiming to be closer to the society, these findings deliver an important insight of science communication through the social media. Although the study delivered several lessons learnt related to science communication through social media studies, it provides an important bases for further studies. Conclusions can support research organizations in improving their science communication.