Exploring morphological innovation and diversification: Analysis of genes involved in gin-trap formation and antenna remodeling during metamorphosis in Tribolium castaneum

How morphological traits originate and diversify is a central question in evolutionary biology. Insects are the most diverse group of animals on the planet and over 80% of insect species belong to the subgroup of holometabola. The shape of a holometabolous insect experiences a striking change during metamorphosis, which allowed the evolution of an overwhelming morphological diversity. Hence, this process provides excellent samples to study the evolution of morphological innovation and diversity. Among insects, the developmental and genetic mechanisms of epidermal patterning are well understood in the model organism, Drosophila melanogaster. However, this highly derived Dipteran species does not show a typical metamorphosis. Drosophila replaces all larval epidermal cells by imaginal cells to form the adult epidermis. Instead, most holometabolous insects re-use larval cells to generate the adult epidermis, In contrast to Drosophila, the red flour beetle, Tribolium castaneum, shows a more typical mode of metamorphosis. Importantly, unbiased large scale RNA interference screening (iBeetle-screen) in Tribolium allows identifying and investigating gene sets involved in the process of morphological innovation and diversification independently from Drosophila knowledge. In the first part of this thesis, the gin-trap was used as a study case to explore how a morphologically novel structure evolved during metamorphosis in Tribolium. Firstly, the wing genes known from Drosophila were investigated for their potential functions in gin-trap formation. The results showed that a large part of the upstream genes but much few downstream genes of the wing gene network were co-opted into gin-trap formation. Secondly, novel genes required for gin-trap development were searched in the iBeetle database. Ten genes were confirmed for their functions in gin-trap formation, most of which were required for wing formation as well. The only gin-trap specific gene, Tc-caspar, which was recruited from another biological context, was required for establishment of the anterior-posterior symmetry of the gin-traps. This is an innovation to this structure. Taken together, these data suggested that gin-traps evolved by co-option of a pruned wing gene regulatory network and a low level of gene recruitment from a distinct biological context. In the second part, novel genes from iBeetle screen were identified and analyzed on antenna metamorphosis in Tribolium. Of the ten confirmed genes, half belonged to the new classifications which were not reported to be associated with antenna patterning in Drosophila. Interestingly, four genes were related to pre-mRNA splicing, indicating the potential role of this process for antenna remodeling. One taxonomically restricted gene was found to affect a specific region of the antenna. And then, I optimized a protocol for whole mount in situ hybridization of pre-pupal antennae and the expression patterns of novel genes showed that the expression patterns were consistent with a role of these genes in antenna remodeling. Finally, I compared the gene sets between antenna and leg development and verified a complex mix of divergence and constraint among these serially homologous appendages. The data obtained in this thesis provide new insight into the morphological innovation and diversification during metamorphosis and are the basis for future studies

JALAD: Joint Accuracy- and Latency-Aware Deep Structure Decoupling for Edge-Cloud Execution

Recent years have witnessed a rapid growth of deep-network based services and applications. A practical and critical problem thus has emerged: how to effectively deploy the deep neural network models such that they can be executed efficiently. Conventional cloud-based approaches usually run the deep models in data center servers, causing large latency because a significant amount of data has to be transferred from the edge of network to the data center. In this paper, we propose JALAD, a joint accuracy- and latency-aware execution framework, which decouples a deep neural network so that a part of it will run at edge devices and the other part inside the conventional cloud, while only a minimum amount of data has to be transferred between them. Though the idea seems straightforward, we are facing challenges including i) how to find the best partition of a deep structure; ii) how to deploy the component at an edge device that only has limited computation power; and iii) how to minimize the overall execution latency. Our answers to these questions are a set of strategies in JALAD, including 1) A normalization based in-layer data compression strategy by jointly considering compression rate and model accuracy; 2) A latency-aware deep decoupling strategy to minimize the overall execution latency; and 3) An edge-cloud structure adaptation strategy that dynamically changes the decoupling for different network conditions. Experiments demonstrate that our solution can significantly reduce the execution latency: it speeds up the overall inference execution with a guaranteed model accuracy loss.Comment: conference, copyright transfered to IEE

Checking of radially sawn Scots pine and Norway spruce wood

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Sound Source Localization and Modeling: Spherical Harmonics Domain Approaches

Sound source localization has been an important research topic in the acoustic signal processing community because of its wide use in many acoustic applications, including speech separation, speech enhancement, sound event detection, automatic speech recognition, automated camera steering, and virtual reality. In the recent decade, there is a growing interest in the research of sound source localization using higher-order microphone arrays, which are capable of recording and analyzing the soundfield over a target spatial area. This thesis studies a novel source feature called the relative harmonic coefficient, that easily estimated from the higher-order microphone measurements. This source feature has direct applications for sound source localization due to its sole dependence on the source position. This thesis proposes two novel sound source localization algorithms using the relative harmonic coefficients: (i) a low-complexity single source localization approach that localizes the source' elevation and azimuth separately. This approach is also appliable to acoustic enhancement for the higher-order microphone array recordings; (ii) a semi-supervised multi-source localization algorithm in a noisy and reverberant environment. Although this approach uses a learning schema, it still has a strong potential to be implemented in practice because only a limited number of labeled measurements are required. However, this algorithm has an inherent limitation as it requires the availability of single-source components. Thus, it is unusable in scenarios where the original recordings have limited single-source components (e.g., multiple sources simultaneously active). To address this issue, we develop a novel MUSIC framework based approach that directly uses simultaneous multi-source recordings. This developed MUSIC approach uses robust measurements of relative sound pressure from the higher-order microphone and is shown to be more suitable in noisy environments than the traditional MUSIC method. While the proposed approaches address the source localization problems, in practice, the broader problem of source localization has some more common challenges, which have received less attention. One such challenge is the common assumption of the sound sources being omnidirectional, which is hardly the case with a typical commercial loudspeaker. Therefore, in this thesis, we analyze the broader problem of analyzing directional characteristics of the commercial loudspeakers by deriving equivalent theoretical acoustic models. Several acoustic models are investigated, including plane waves decomposition, point source decomposition, and mixed source decomposition. We finally conduct extensive experimental examinations to see which acoustic model has more similar characteristics with commercial loudspeakers