Abstract
Sound design has been a fundamental component of audiovisual storytelling in linear media. However, with recent technological developments and the shift towards non-linear and immersive media, things are rapidly changing. More sensory information is available and, at the same time, the user is gaining agency upon the narrative, being offered the possibility of navigating or making other decisions. These new characteristics of immersive environments bring new challenges to storytelling in interactive narratives and require new strategies and techniques for audiovisual narrative progression. Can technology offer an immersive environment where the user has the sensation of agency, of choice, where her actions are not mediated by evident controls but subliminally induced in a way that it is ensured that a narrative is being followed? Can sound be a subliminal element that induces attentional focus on the most relevant elements for the narrative, inducing storytelling and biasing search in an immersive non-linear audiovisual environment? Herein, we present a literature review that has been guided by this prospect. With these questions in view, we present our exploration process in finding possible answers and potential solution paths. We point out that consistency, in terms of coherency across sensory modalities and emotional matching may be a critical aspect. Finally, we consider that this review may open up new paths for experimental studies that could, in the future, provide new strategies in the practice of sound design in the context of non-linear media.

Abstract
Since the beginning of the XXI century, we have been witnessing a significant shift in the media landscape towards enhanced immersive audiovisual manifestations, from controlled research environments to gradual production market penetration. Virtual reality, augmented reality, mixed reality, extended reality, 360 degrees video, and digital games are representative examples of these immersive technologies. Spatial audio design and production are instrumental to the immersive experience. As Ambisonics techniques do potentially mean more expense - in memory, processing power, and production budget -, limited exploration in the development of new composition and production methodologies across popular music production has been considered beyond the traditional stereophonic format. Our work details a post-production case study using spatial audio, namely High Order Ambisonics. The case study is a Brazilian popular song, remixed using 3rd order Ambisonics from a multitrack recording session composed of monophonic and stereophonic audio tracks. The song encompasses a unique approach for audio spatialization guided by hierarchical audio content attributes across multiple structural time scales and musical contexts. The evaluation of our production process adopted iterative heuristic assessments comparing technical decisions and aesthetic intentions in fostering an augmented spatial audio song. A set of technical guidelines and good practices on how and why to positioning audio in space are abstracted from our case study evaluation, which critically advances the theory and practice of popular musical audio production in immersive technologies.

Abstract

Abstract
Sap flow measurements of trees are today the most common method to determine evapotranspiration at the tree and the forest/crop canopy level. They provide independent measurements for flux comparisons and model validation. The most common approach to measure the sap flow is based on intrusive solutions with heaters and thermal sensors. This sap flow sensor technology is not very reliable for more than one season crop; it is intrusive and not adequate for low diameter trunk trees. The non-invasive methods comprise mostly Radio-frequency (RF) technologies, typically using satellite or air-born sources. This system can monitor large fields but cannot measure sap levels of a single plant (precision agriculture). This article studies the hypothesis to use of RF signals attenuation principle to detect variations in the quantity of water present in a single plant. This article presents a well-defined experience to measure water content in leaves, by means of high gains RF antennas, spectrometer, and a robotic arm. Moreover, a similar concept is studied with an off-the-shelf radar solution-for the automotive industry-to detect changes in the water presence in a single plant and leaf. The conclusions indicate a novel potential application of this technology to precision agriculture as the experiments data is directly related to the sap flow variations in plant.

Abstract
Ocean related activities are often supported by offshore equipment with particular power demands. These are usually deployed at remote locations and have limited space, thus small energy harvesting technologies, such as photovoltaic panels or wind turbines, are used to power their instruments. However, the inherent energy sources are intermittent and have lower density and predictability than an alternative source: wave energy. Here, we propose and critically assess triboelectric nanogenerators (TENGs) as a promising technology for integration into wave buoys. Three TENGs based on rolling-spheres were developed and their performance compared in both a "dry" bench testing system under rotating motions, and in a large-scale wave basin under realistic sea-states installed within a scaled navigation buoy. Both experiments show that the electrical outputs of these TENGs increase with decreasing wave periods and increasing wave amplitudes. However, the wave basin tests clearly demonstrated a significant dependency of the electrical outputs on the pitch degree of freedom and the need to take into account the full dynamics of the buoy, and not only that of TENGs, when subjected to the excitations of waves. This work opens new horizons and strategies to apply TENGs in marine applications, considering realistic hydrodynamic behaviors of floating bodies.

Abstract
In this paper, we address a subtopic of the broad domain of audio enhancement, namely musical audio bandwidth extension. We formulate the bandwidth extension problem using deep neural networks, where a band-limited signal is provided as input to the network, with the goal of reconstructing a full-bandwidth output. Our main contribution centers on the impact of the choice of low-pass filter when training and subsequently testing the network. For two different state-of-the-art deep architectures, ResNet and U-Net, we demonstrate that when the training and testing filters are matched, improvements in signal-to-noise ratio (SNR) of up to 7 dB can be obtained. However, when these filters differ, the improvement falls considerably and under some training conditions results in a lower SNR than the band-limited input. To circumvent this apparent overfitting to filter shape, we propose a data augmentation strategy which utilizes multiple low-pass filters during training and leads to improved generalization to unseen filtering conditions at test time.