Induction of grape botrytization during withering affects volatile composition of Recioto di Soave, a “passito”-style wine

The influence of noble rot on the quality of Recioto di Soave, a “passito” sweet white wine, is greatly variable depending on the occurrence of favourable seasonal conditions for the mould infection. Botrytized wines were produced from grapes inoculated with conidia suspensions to evaluate the effects of noble rot on volatile compounds profile of Recioto di Soave wine. Different development stages of Botrytis cinerea and degree of grape withering were ascertained by must analysis. Several volatile components were involved in marked changes depending on the infection and grape withering level. Fruity esters, carbonyl compounds, phenols, lactones and acetamides greatly changed among botrytized wines. The results demonstrated that the level of B. cinerea infection and the degree of grape withering exert considerable influence on the volatile composition of this sweet wine. Strain-dependent effects were also preliminary ascertained. The process of induction of grape botrytization presented in this study could be recommendable for the industrial production of botrytized Recioto di Soave wine.     

Semi-quantitative monitoring of confluence of adherent mesenchymal stromal cells on calcium-phosphate granules by using widefield microscopy images

The analysis of cell confluence and proliferation is essential to design biomaterials and scaffolds to use as bone substitutes in clinical applications. Accordingly, several approaches have been proposed in the literature to estimate the area of the scaffold covered by cells. Nevertheless, most of the approaches rely on sophisticated equipment not employed for routine analyses, while the rest of them usually do not provide significant statistics about the cell distribution. This research aims at studying confluence and proliferation of mesenchymal stromal cells (MSC) adherent on OSPROLIFE^®, a commercial biomaterial in the form of granules. In particular, we propose a Computer Vision approach that can routinely be employed to monitor the surface of the single granules covered by cells because only a standard widefield fluorescent microscope is required. In order to acquire significant statistics data, we analyse wide-area images built by using MicroMos v2.0, an updated version of a previously published software specific for stitching brightfield and phase-contrast images manually acquired via a widefield microscope. In particular, MicroMos v2.0 permits to build accurate “mosaics” of fluorescent images, after correcting vignetting and photo-bleaching effects, providing a consistent representation of a sample region containing numerous granules. Then, our method allows to make automatically a statistically significant estimate of the percentage of the area of the single granules covered by cells. Finally, by analysing hundreds of granules at different time intervals we also obtained reliable data regarding cell proliferation, confirming that not only MSC adhere onto the OSPROLIFE^® granules, but even proliferate over time.     

Modeling sleep mode gains in energy-aware networks

Nowadays two main approaches are being pursued to reduce energy consumption of networks: the use of sleep modes in which devices enter a low-power state during inactivity periods, and the adoption of energy proportional mechanisms where the device architecture is designed to make energy consumption proportional to the actual load. Common to all the proposals is the evaluation of energy saving performance by means of simulation or experimental evidence, which typically consider a limited set of benchmarking scenarios.     

Hierarchical mesh segmentation based on fitting primitives

In this paper, we describe a hierarchical face clustering algorithm for triangle meshes based on fitting primitives belonging to an arbitrary set. The method proposed is completely automatic, and generates a binary tree of clusters, each of which is fitted by one of the primitives employed. Initially, each triangle represents a single cluster; at every iteration, all the pairs of adjacent clusters are considered, and the one that can be better approximated by one of the primitives forms a new single cluster. The approximation error is evaluated using the same metric for all the primitives, so that it makes sense to choose which is the most suitable primitive to approximate the set of triangles in a cluster. Based on this approach, we have implemented a prototype that uses planes, spheres and cylinders, and have experimented that for meshes made of 100 K faces, the whole binary tree of clusters can be built in about 8 s on a standard PC. The framework described here has natural application in reverse engineering processes, but it has also been tested for surface denoising, feature recovery and character skinning.     

Globally convergent autocalibration using interval analysis

We address the problem of autocalibration of a moving camera with unknown constant intrinsic parameters. Existing autocalibration techniques use numerical optimization algorithms whose convergence to the correct result cannot be guaranteed, in general. To address this problem, we have developed a method where an interval branch-and-bound method is employed for numerical minimization. Thanks to the properties of interval analysis this method converges to the global solution with mathematical certainty and arbitrary accuracy and the only input information it requires from the user are a set of point correspondences and a search interval. The cost function is based on the Huang-Faugeras constraint of the essential matrix. A recently proposed interval extension based on Bernstein polynomial forms has been investigated to speed up the search for the solution. Finally, experimental results are presented.     

Fabrication of photoactive heterostructures based on quantum dots decorated with Au nanoparticles

Silica based multifunctional heterostructures, exhibiting near infrared (NIR) absorption (650–1200 nm) and luminescence in the visible region, represent innovative nanosystems useful for diagnostic or theranostic applications. Herein, colloidal synthetic procedures are applied to design a photoactive multifunctional nanosystem. Luminescent silica (SiO₂) coated quantum dots (QDs) have been used as versatile nanoplatforms to assemble on their surface gold (Au) seeds, further grown into Au spackled structures. The synthesized nanostructures combine the QD emission in the visible region, and, concomitantly, the distinctive NIR absorption of Au nanodomains. The possibility of having multiple QDs in a single heterostructure, the SiO₂ shell thickness, and the extent of Au deposition onto SiO₂ surface have been carefully controlled. The work shows that a single QD entrapped in 16 nm thick SiO₂ shell, coated with Au speckles, represents the most suitable geometry to preserve the QD emission in the visible region and to generate NIR absorption from metal NPs. The resulting architectures present a biomedical potential as an effective optical multimodal probes and as promising therapeutic agents due to the Au NP mediated photothermal effect.     

Geographic knowledge extraction and semantic similarity in OpenStreetMap

In recent years, a web phenomenon known as Volunteered Geographic Information (VGI) has produced large crowdsourced geographic data sets. OpenStreetMap (OSM), the leading VGI project, aims at building an open-content world map through user contributions. OSM semantics consists of a set of properties (called ‘tags’) describing geographic classes, whose usage is defined by project contributors on a dedicated Wiki website. Because of its simple and open semantic structure, the OSM approach often results in noisy and ambiguous data, limiting its usability for analysis in information retrieval, recommender systems and data mining. Devising a mechanism for computing the semantic similarity of the OSM geographic classes can help alleviate this semantic gap. The contribution of this paper is twofold. It consists of (1) the development of the OSM Semantic Network by means of a web crawler tailored to the OSM Wiki website; this semantic network can be used to compute semantic similarity through co-citation measures, providing a novel semantic tool for OSM and GIS communities; (2) a study of the cognitive plausibility (i.e. the ability to replicate human judgement) of co-citation algorithms when applied to the computation of semantic similarity of geographic concepts. Empirical evidence supports the usage of co-citation algorithms—SimRank showing the highest plausibility—to compute concept similarity in a crowdsourced semantic network.