83 research outputs found

    From Technological Investigation and Software Emulation to Music Analysis: An integrated approach to Barry Truax's Riverrun

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    This paper presents an approach to studying Barry Truax’s Riverrun as it is being carried out within the TaCEM project (Technology and Creativity in Electroacoustic Music), a collaboration between the Universities of Huddersfield and Durham funded for 30 months (2012-2015) by the Arts and Humanities Research Council in the United Kingdom. This approach aims at realising an Interactive Aural Analysis with which the user can explore the creative and technological environment used by the composer to build his oeuvre, as well as navigate aurally through the results of the musicological study. It involves an important technological investigation of Truax’s GSX program for digital granular synthesis, leading to the implementation, in the Max environment, of emulation software allowing for the live recreation of each of Riverrun’s sequences, along with further tools dedicated to the musical analysis of the piece. This paper presents the technological investigation and its issues, the pieces of software for the Interactive Aural Analysis of the work, and musicological observations drawn from such an approach

    Sample-level sound synthesis with recurrent neural networks and conceptors

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    Conceptors are a recent development in the field of reservoir computing; they can be used to influence the dynamics of recurrent neural networks (RNNs), enabling generation of arbitrary patterns based on training data. Conceptors allow interpolation and extrapolation between patterns, and also provide a system of boolean logic for combining patterns together. Generation and manipulation of arbitrary patterns using conceptors has significant potential as a sound synthesis method for applications in computer music but has yet to be explored. Conceptors are untested with the generation of multi-timbre audio patterns, and little testing has been done on scalability to longer patterns required for audio. A novel method of sound synthesis based on conceptors is introduced. Conceptular Synthesis is based on granular synthesis; sets of conceptors are trained to recall varying patterns from a single RNN, then a runtime mechanism switches between them, generating short patterns which are recombined into a longer sound. The quality of sound resynthesis using this technique is experimentally evaluated. Conceptor models are shown to resynthesise audio with a comparable quality to a close equivalent technique using echo state networks with stored patterns and output feedback. Conceptor models are also shown to excel in their malleability and potential for creative sound manipulation, in comparison to echo state network models which tend to fail when the same manipulations are applied. Examples are given demonstrating creative sonic possibilities, by exploiting conceptor pattern morphing, boolean conceptor logic and manipulation of RNN dynamics. Limitations of conceptor models are revealed with regards to reproduction quality, and pragmatic limitations are also shown, where rises in computation and memory requirements preclude the use of these models for training with longer sound samples. The techniques presented here represent an initial exploration of the sound synthesis potential of conceptors, demonstrating possible creative applications in sound design; future possibilities and research questions are outlined

    Neuronal networks which underlie Impaired Awareness of Hypoglycaemia

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    Integrating bioprocesses into industrial complexes for sustainable development

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    The objective of this research is to propose, develop and demonstrate a methodology for the optimal integration of bioprocesses in an existing chemical production complex. Chemical complex optimization is determining the optimal configuration of chemical plants in a superstructure of possible plants based on economic, environmental and sustainable criteria objective function (triple bottomline) and solves a mixed integer non linear programming problem. This research demonstrated the transition of production of chemicals from non-renewable to renewable feedstock. A conceptual design of biochemical processes was converted to five industrial scale designs in Aspen HYSYS® process simulator. Fourteen input-output block models were created from the designs based on the mass and energy relations. A superstructure of plants was formed by integrating the bioprocess models into a base case of existing plants in the lower Mississippi River corridor. Carbon dioxide produced from the integrated complex was used for algae oil and new chemicals production. The superstructure had 978 equality constraints, 91 inequality constraints, 969 continuous variables and 25 binary variables. The optimal solution gave a triple bottomline profit of 1,650millionperyearfromthebasecasesolutionof1,650 million per year from the base case solution of 854 million per year (93% increase). Raw material costs in the optimal solution decreased by 31% due to the exclusion of the costly ethylbenzene process. The utility costs for the complex increased to 46millionperyearfrom46 million per year from 12 million per year. The sustainable costs to the society decreased to 10millionperyearfrom10 million per year from 18 million per year (44% decrease). The bioprocesses increased the pure carbon dioxide sources to 1.07 million metric tons per year from 0.75 million metric tons per year for the base case (43% increase). The pure carbon dioxide vented to the atmosphere was reduced to zero in the optimal structure from 0.61 million metric tons per year (100% decrease) by consumption in the complex. The methodology can be used by decision makers to evaluate energy efficient and environmentally acceptable plants and have new products from greenhouse gases. Based on these results, the methodology could be applied to other chemical complexes in the world for reduced emissions and energy savings

    Comparative Analysis of Selenocysteine Machinery and Selenoproteome Gene Expression in Mouse Brain Identifies Neurons as Key Functional Sites of Selenium in Mammals

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    Although dietary selenium (Se) deficiency results in phenotypes associated with selenoprotein depletion in various organs, the brain is protected from Se loss. To address the basis for the critical role of Se in brain function, we carried out comparative gene expression analyses for the complete selenoproteome and associated biosynthetic factors. Using the Allen Brain Atlas, we evaluated 159 regions of adult mouse brain and provided experimental analyses of selected selenoproteins. All 24 selenoprotein mRNAs were expressed in the mouse brain. Most strikingly, neurons in olfactory bulb, hippocampus, cerebral cortex, and cerebellar cortex were exceptionally rich in selenoprotein gene expression, in particular in GPx4, SelK, SelM, SelW, and Sep15. Over half of the selenoprotein genes were also expressed in the choroid plexus. A unique expression pattern was observed for one of the highly expressed selenoprotein genes, SelP, which we suggest to provide neurons with Se. Cluster analysis of the expression data linked certain selenoproteins and selenocysteine machinery genes and suggested functional linkages among selenoproteins, such as that between SelM and Sep15. Overall, this study suggests that the main functions of selenium in mammals are confined to certain neurons in the brain

    Estabelecimento e estudo cinético do processo de desamonificaçao utilizando-se um reator único para remoção de nitrogênio à temperatura ambiente

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    Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Química, Florianópolis, 2013.2014-08-06T17:17:31
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