1,201 research outputs found
Mapping the dielectric properties of unknown targets by using a network of microwave sensors: A proof-of-concept
The subject of this paper is the possible use of a network of microwave sensors to achieve a map of the electromagnetic properties of unknown targets. The basic idea is to use a set of microwave sensors to illuminate a region of interest and to measure the resulting axial component of the electric field. Measurements are then processed by means of a technique based on inverse-scattering, which provides an estimate map of the dielectric values of the area under examination, allowing to discriminate among possible targets. In order to initially evaluate the feasibility of the proposed approach, numerical results in a simulated environment are preliminarily considered and discussed. Furthermore, an initial test on experimental data in a simplified configuration is also presented
Characterization of Cell-Envelope Proteinases from Two Lacticaseibacillus casei Strains Isolated from Parmigiano Reggiano Cheese
Microbial Consortia Involved in Traditional Sicilian Sourdough: Characterization of Lactic Acid Bacteria and Yeast Populations
Low Power Front End for the Optical Module of a Neutrino Underwater Telescope
A proposal for a new system to capture signals in the Optical Module (OM) of an underwater neutrino telescope is described. It concentrates on the problem of power consumption and time precision. In particular, a solution for the interface between the photomultiplier (PMT) and the front-end electronics is presented
Biotransformation of Chloroaromatics: the Impact of Bioavailability and Substrate Specificity.
FoodOmics as a new frontier to reveal microbial community and metabolic processes occurring on table olives fermentation
Table olives are considered the most widespread fermented food in the Mediterranean area and their consumption is expanding all over the world. This fermented vegetable can be considered as a natural functional food thanks to their high nutritional value and high content of bioactive compounds that contribute to the health and well-being of consumers. The presence of bioactive compounds is strongly influenced by a complex microbial consortium, traditionally exploited through culture-dependent approaches. Recently, the rapid spread of omics technologies has represented an important challenge to better understand the function, the adaptation and the exploitation of microbial diversity in different complex ecosystems, such as table olives. This review provides an overview of the potentiality of omics technologies to in depth investigate the microbial composition and the metabolic processes that drive the table olives fermentation, affecting both sensorial profile and safety properties of the final product. Finally, the review points out the role of omics approaches to raise at higher sophisticated level the investigations on microbial, gene, protein, and metabolite, with huge potential for the integration of table olives composition with functional assessments
Metabolomic and Transcriptional Profiling of Oleuropein Bioconversion into Hydroxytyrosol during Table Olive Fermentation by Lactiplantibacillus plantarum
Proposal, development and test of an analog front-end electronic board for Nemo telescope
The NEMO collaboration is involved in the R&D of the main technologies for the project of a km3 scale underwater neutrino telescope. The proposed detector is made up of thousands of Optical Modules (hereafter OM), spread over the entire volume for Cˇ erenkov light detection. Each OMis equipped with a photo multiplier tube (PMT) and an electronic circuit for data acquisition and transmission (DAQ-Board). This work points out the possible benefits of a hybrid solution based on an analog ASIC (Application Specific Integrated Circuit) employed for the analog signal acquisition and an FPGA (Field Programmable Gate Array), a digital programmable IC (Integrated Circuit) which performs the data acquisition and the data transmission
Comparative study of protective coatings for the conservation of Urban Art
Contemporary mural paintings are complex artworks for several reasons, including the heterogeneity of the materials used to make them, and the different types of substrate on which the painting layers can be applied. Currently we are focused on a technical-scientific research aimed to solve the issues related to the long-term care and maintenance of murals, by evaluating the performance of several protective coatings applied on these artworks. This paper deals with a preliminary experimentation aimed to: (a) study the interaction of antigraffiti products on common synthetic paints; (b) test the effectiveness and efficiency of several commercial products used as antigraffiti; (c) define of the best procedure to remove vandalism spray from a coated surface, without damaging the underlying painting layers. Tests have been carried out on laboratory specimens and the performances of different antigraffiti agents have been evaluated by optical and electron microscope observations, as well as by colorimetric measurements
A Robust SVM Color-Based Food Segmentation Algorithm for the Production Process of a Traditional Carasau Bread
In this paper, we address the problem of automatic image segmentation methods applied to the partial automation of the production process of a traditional Sardinian flatbread called pane Carasau for assuring quality control. The study focuses on one of the most critical activities for obtaining an efficient degree of automation: the estimation of the size and shape of the bread sheets during the production phase, to study the shape variations undergone by the sheet depending on some environmental and production variables. The knowledge can thus be used to create a system capable of predicting the quality of the shape of the dough produced and empower the production process. We implemented an image acquisition system and created an efficient machine learning algorithm, based on support vector machines, for the segmentation and estimation of image measurements for Carasau bread. Experiments demonstrated that the method can successfully achieve accurate segmentation of bread sheets images, ensuring that the dimensions extracted are representative of the sheets coming from the production process. The algorithm proved to be fast and accurate in estimating the size of the bread sheets in various scenarios that occurred over a year of acquisitions. The maximum error committed by the algorithm is equal to the 2.2% of the pixel size in the worst scenario and to 1.2% elsewhere
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