Edison (Italy)

In Italia la superficie dei rimboschimenti ammonta a circa mezzo milione di ettari, la maggior parte dei quali a prevalenza di conifere. Negli ultimi decenni sono emerse problematiche riguardanti la potenziale instabilità di questi soprassuoli, spesso causata da una gestione selvicolturale mancante o insufficiente e discontinua. Questa comunicazione sintetizza i risultati di uno studio sulle modalità di gestione selvicolturale per la valorizzazione dei rimboschimenti di pino nero e pino laricio e delle piantagioni di douglasia in Italia. Utilizzando i dati dell’inventario forestale nazionale e i dati di parcelle sperimentali sono stati simulati con il modello 3D-CMCC-FEM vari regimi di diradamento per determinare il grado di intensità e l’intervallo di ripetizione degli interventi. Questi risultati sono stati utilizzati per stimare la fornitura di alcune utilità ecosistemiche e quantificarne il valore economico. È stato inoltre elaborato un indice per quantificare la densità di coltivazione dei rimboschimenti al fine di ottimizzare la produttività in termini di massa legnosa. Alla luce dei risultati ottenuti, in questa comunicazione sono infine riportate alcune indicazioni operative per la gestione selvicolturale dei rimboschimenti delle specie considerate.

This protocol describes day 2 of our workflow to grow worms in liquid culture to induce the production of natural products (in this case, 1-HP derivatives). In this protocol, we get an approximate count for the number of life-stage synchronized worms we have, ensure to concentrate them to 30,000 worms/ml, and provide E.coli OP50 for them to be able to progress

This abstract describes how to bleach/synchronize a large mixed-stage population of C. elegans grown on Large Scale Culture Plates (LSCP). For more information on LSCPs, refer to Shaver et al., 2021.

The energy performance certificate (EPC) is a document that certifies the average annual energy consumption of a building in standard conditions and allows it to be classified within a so-called energy class. In a period such as this, when greenhouse gas emissions are of considerable importance and where the objective is to improve energy security and reduce energy costs in our cities, energy certification has a key role to play. The proposed work aims to model and characterize residential buildings’ energy efficiency by exploring heterogeneous, geo-referenced data with different spatial and temporal granularity. The paper presents TUCANA (TUrin Certificates ANAlysis), an innovative data mining engine able to cover the whole analytics workflow for the analysis of the energy performance certificates, including cluster analysis and a model generalization step based on a novel spatial constrained K-NN, able to automatically characterize a broad set of buildings distributed across a major city and predict different energy-related features for new unseen buildings. The energy certificates analyzed in this work have been issued by the Piedmont Region (a northwest region of Italy) through open data. The results obtained on a large dataset are displayed in novel, dynamic, and interactive geospatial maps that can be consulted on a web application integrated into the system. The visualization tool provides transparent and human-readable knowledge to various stakeholders, thus supporting the decision-making process.

Brain ConnectivityVol. 10, No. 6 EditorialBrain Connectivity: Advances in Neurodegenerative DiseasesPaul EdisonPaul EdisonPaul Edison, Imperial College London Search for more papers by this authorPublished Online:18 Aug 2020https://doi.org/10.1089/brain.2020.29012.pedAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"Brain Connectivity: Advances in Neurodegenerative Diseases." Brain Connectivity, 10(6), pp. 251–252FiguresReferencesRelatedDetails Volume 10Issue 6Aug 2020 InformationCopyright 2020, Mary Ann Liebert, Inc., publishersTo cite this article:Paul Edison.Brain Connectivity: Advances in Neurodegenerative Diseases.Brain Connectivity.Aug 2020.251-252.http://doi.org/10.1089/brain.2020.29012.pedPublished in Volume: 10 Issue 6: August 18, 2020PDF download

Hybrid structures composed of layered one-dimensional (1D) and two-dimensional (2D) materials opened new perspectives and opportunities through the build-up of hetero-junctions with versatile layered structures and led to fascinating fundamental phenomena and advanced devices. We succeeded in depositing by magnetron sputtering vertically aligned 1D ZnO nanorods on 2D MoS2 flakes obtained by exfoliation, preserving the structure of the 2D materials. The photoluminescence (PL) optical properties of the hybrid structure were assessed towards developing a contactless optical chemical sensor.

Edison is Europe’s oldest energy company and one of the largest utilities in Italy. Since the ’90s the Company has played a leading role in the energy sector, by investing in the most advanced and clean technologies and providing a key contribution to the liberalisation of the Italian electricity and gas markets. Today, Edison’s vision of the future relies on sustainable power generation, energy efficiency and high-value relationship with customers and territories. Indeed, the Company has constantly upgraded and innovated its generation fleet, expanded its renewables portfolio, and consolidated its expertise in the gas and electricity supply chain in order to support the energy transition until sustainable end uses like mobility. Moreover, following the liberalisation process, Edison has developed a wide range of energy products and services, increasing its presence in the downstream markets–creating shared value for the local communities–while continuously improving the efficiency and sustainability of the upstream phase.

Brain ConnectivityVol. 9, No. 8 EditorialA Note from Our New Editor-in-ChiefPaul EdisonPaul EdisonPaul Edison, Imperial College LondonSearch for more papers by this authorPublished Online:17 Oct 2019https://doi.org/10.1089/brain.2019.29002.pedAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"A Note from Our New Editor-in-Chief." Brain Connectivity, 9(8), p. 593FiguresReferencesRelatedDetails Volume 9Issue 8Oct 2019 InformationCopyright 2019, Mary Ann Liebert, Inc., publishersTo cite this article:Paul Edison.A Note from Our New Editor-in-Chief.Brain Connectivity.Oct 2019.593-593.http://doi.org/10.1089/brain.2019.29002.pedPublished in Volume: 9 Issue 8: October 17, 2019PDF download

We present a novel method for concept drift detection, based on: 1) the development and continuous updating of online sequential extreme learning machines (OS-ELMs) and 2) the quantification of how much the updated models are modified by the newly collected data. The proposed method is verified on two synthetic case studies regarding different types of concept drift and is applied to two public real-world data sets and a real problem of predicting energy production from a wind plant. The results show the superiority of the proposed method with respect to alternative state-of-the-art concept drift detection methods. Furthermore, updating the prediction model when the concept drift has been detected is shown to allow improving the overall accuracy of the energy prediction model and, at the same time, minimizing the number of model updatings.