Publications by authors named "C Maurizio"

This study explores the use of conductive material in scaling up anaerobic digestion for enhanced biogas production. Focusing on Direct Interspecies Electron Transfer (DIET), the research employs a syntrophic DIET-able consortium formed by Shewanella oneidensis and Methanosarcina barkerii in 3.8-L experiments utilizing reticulated vitreous carbon (RVC) as conductive material.

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Article Synopsis
  • The Italian Society of Echography and Cardiovascular Imaging (SIECVI) conducted a national survey to investigate stress echocardiography (SE) practices across Italy, collecting data from 228 laboratories in November 2022.
  • The survey revealed that out of 179 centers performing SE, most were located in northern Italy, and the study categorized them into low, moderate, and high volume of activity based on the number of SE examinations.
  • Key findings indicated differences in the use of stressors, with a tendency for high-volume centers to employ multiple stress techniques and incorporate advanced evaluations like coronary flow velocity reserve (CFVR) more frequently than low and moderate volume centers.
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The transfer of photogenerated charges through interfaces in heterojunction photoanodes is a key process that controls the efficiency of solar water splitting. Considering CoO/SiO/Si photoanodes prepared by physical vapor deposition as a representative case study, it is shown that defects normally present in the native SiO layer dramatically affect the onset of the photocurrent. Electron paramagnetic resonance indicates that the signal of defects located in dangling bonds of trivalent Si atoms at the Si/SiO interface vanishes upon vacuum annealing at 850 °C.

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Background: The Italian Society of Echocardiography and Cardiovascular Imaging (SIECVI) conducted a national survey to understand better how different echocardiographic modalities are used and accessed in Italy.

Methods: We analyzed echocardiography laboratory activities over a month (November 2022). Data were retrieved via an electronic survey based on a structured questionnaire, uploaded on the SIECVI website.

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Article Synopsis
  • - The increasing popularity of microbiome studies is enhanced by machine learning techniques, specifically focusing on the effectiveness of Association Rule Mining (ARM) for extracting microbial patterns from 16S rRNA metabarcoding data.
  • - The study examines the challenges of handling large datasets generated by ARM, emphasizing the importance of careful input selection and use of metadata in pattern extraction.
  • - To aid researchers, the authors developed microFIM, a Python tool that streamlines the ARM process and integrates common microbiome outputs to improve data analysis and visualization capabilities.
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