Publications by authors named "Davide Perini"
In this paper, we propose a data-driven approach for the reconstruction of unknown room impulse responses (RIRs) based on the deep prior paradigm. We formulate RIR reconstruction as an inverse problem. More specifically, a convolutional neural network (CNN) is employed prior, in order to obtain a regularized solution to the RIR reconstruction problem for uniform linear arrays.
View Article and Find Full Text PDFArticle Synopsis
- Recent studies have significantly increased on microbial lipid biosynthesis, focusing on oleaginous yeasts that can store lipids up to 60-70% of their dry weight, which could be used for biofuels and other chemical products.
- A large-scale screening identified several yeast strains with varying lipid yields and fatty acid profiles based on temperature and carbon sources, with some strains showing impressive productivity metrics.
- The findings emphasize the need to further explore diverse yeast species for their lipid accumulation potential, highlighting their strategic importance in producing valuable oleochemical products.
Background And Aims: The assessment of the genetic variability and the identification of isolated populations within a given species represent important information to plan conservation strategies on a genetic basis. In this work, the genetic variability in five natural populations of Juniperus phoenicea, three from Sardinia, one from Cyprus and the last one in the Maritime Alps was analysed by means of ISSRs, on the hypothesis that the latter could have been a refugial one during the last glaciation.
Methods: ISSRs were chosen because of their ability to detect variation without any prior sequence information.