Roadmap on Label-Free Super-resolution Imaging

Label-free super-resolution (LFSR) imaging relies on light-scattering processes in nanoscale objects without a need for fluorescent (FL) staining required in super-resolved FL microscopy. The objectives of this Roadmap are to present a comprehensive vision of the developments, the state-of-the-art in this field, and to discuss the resolution boundaries and hurdles that need to be overcome to break the classical diffraction limit of the label-free imaging. The scope of this Roadmap spans from the advanced interference detection techniques, where the diffraction-limited lateral resolution is combined with unsurpassed axial and temporal resolution, to techniques with true lateral super-resolution capability that are based on understanding resolution as an information science problem, on using novel structured illumination, near-field scanning, and nonlinear optics approaches, and on designing superlenses based on nanoplasmonics, metamaterials, transformation optics, and microsphere-assisted approaches. To this end, this Roadmap brings under the same umbrella researchers from the physics and biomedical optics communities in which such studies have often been developing separately. The ultimate intent of this paper is to create a vision for the current and future developments of LFSR imaging based on its physical mechanisms and to create a great opening for the series of articles in this field.Peer reviewe

The Mozart Expositional Punctuation Corpus: A Dataset of Interthematic Cadences in Mozart's Sonata-Allegro Exposition

This report documents a dataset consisting of expert annotations (symbolic data) of interthematic (higher-level) cadences in the exposition sections of all of Mozart's instrumental sonata-allegro movements

A Deep Learning Approach to Unsupervised Ensemble Learning

Abstract We show how deep learning methods can be applied in the context of crowdsourcing and unsupervised ensemble learning. First, we prove that the popular model of Dawid and Skene, which assumes that all classifiers are conditionally independent, is equivalent to a Restricted Boltzmann Machine (RBM) with a single hidden node. Hence, under this model, the posterior probabilities of the true labels can be instead estimated via a trained RBM. Next, to address the more general case, where classifiers may strongly violate the conditional independence assumption, we propose to apply RBM-based Deep Neural Net (DNN). Experimental results on various simulated and real-world datasets demonstrate that our proposed DNN approach outperforms other state-of-the-art methods, in particular when the data violates the conditional independence assumption

Table_3_Comparative genomics of Bacillus cereus sensu lato spp. biocontrol strains in correlation to in-vitro phenotypes and plant pathogen antagonistic capacity.xlsx

Bacillus cereus sensu lato (Bcsl) strains are widely explored due to their capacity to antagonize a broad range of plant pathogens. These include B. cereus sp. UW85, whose antagonistic capacity is attributed to the secondary metabolite Zwittermicin A (ZwA). We recently isolated four soil and root-associated Bcsl strains (MO2, S−10, S-25, LSTW-24) that displayed different growth profiles and in-vitro antagonistic effects against three soilborne plant pathogens models: Pythium aphanidermatum (oomycete) Rhizoctonia solani (basidiomycete), and Fusarium oxysporum (ascomycete). To identify genetic mechanisms potentially responsible for the differences in growth and antagonistic phenotypes of these Bcsl strains, we sequenced and compared their genomes, and that of strain UW85 using a hybrid sequencing pipeline. Despite similarities, specific Bcsl strains had unique secondary metabolite and chitinase-encoding genes that could potentially explain observed differences in in-vitro chitinolytic potential and anti-fungal activity. Strains UW85, S-10 and S-25 contained a (~500 Kbp) mega-plasmid that harbored the ZwA biosynthetic gene cluster. The UW85 mega-plasmid contained more ABC transporters than the other two strains, whereas the S-25 mega-plasmid carried a unique cluster containing cellulose and chitin degrading genes. Collectively, comparative genomics revealed several mechanisms that can potentially explain differences in in-vitro antagonism of Bcsl strains toward fungal plant pathogens.</p