FROM 3D SURVEYING DATA TO BIM TO BEM: THE INCUBE DATASET

In recent years, the improvement of sensors and methodologies for 3D reality-based surveying has exponentially enhanced the possibility of creating digital replicas of the real world. LiDAR technologies and photogrammetry are currently standard approaches for collecting 3D geometric information of indoor and outdoor environments at different scales. This information can potentially be part of a broader processing workflow that, starting from 3D surveyed data and through Building Information Models (BIM) generation, leads to more complex analyses of buildings’ features and behavior (Figure 1). However, creating BIM models, especially of historic and heritage assets (HBIM), is still resource-intensive and time-consuming due to the manual efforts required for data creation and enrichment. Improve 3D data processing, interoperability, and the automation of the BIM generation process are some of the trending research topics, and benchmark datasets are extremely helpful in evaluating newly developed algorithms and methodologies for these scopes. This paper introduces the InCUBE dataset, resulting from the activities of the recently funded EU InCUBE project, focused on unlocking the EU building renovation through integrated strategies and processes for efficient built-environment management (including the use of innovative renewable energy technologies and digitalization). The set of data collects raw and processed data produced for the Italian demo site in the Santa Chiara district of Trento (Italy). The diversity of the shared data enables multiple possible uses, investigations and developments, and some of them are presented in this contribution

How can ski resorts get smart? Transdisciplinary approaches to sustainable winter tourism in the European Alps

Climate change and the call for reduction of greenhouse gas emissions, the efficient use of (renewable) energy, and more resilient winter tourism regions, forces ski resorts across the European Alps to look for \u201csmart\u201d approaches to transition towards a sustainable, low-carbon economy. Drawing on the smart-city concept and considering the different historical developments of Alpine resorts, the Smart Altitude Decision-Making Toolkit was developed using a combination of an energy audit tool, a WebGIS, and collaborative and innovative living labs installed in Les Orres (France), Madonna di Campiglio (Italy), Krvavec (Slovenia), and Verbier (Switzerland). This step-by-step Decision-Making Toolkit enables ski resorts to get feedback on their energy demand, an overview of the locally available sources of renewable energy, and insights regarding their potential for improving their energy efficiency by low-carbon interventions. The Decision-Making Toolkit is suitable for knowledge transfer between stakeholders within living labs and moreover provides the flexibility for tailor-made low-carbon strategies adapting to the unique assets and situatedness of ski resorts

Anesthetic management during endocardial radiofrequency ablation of septal hypertrophy – a case report

Background: Hypertrophic cardiomyopathy (HCM) is a genetic disorder present in up to 1/500 individuals, about 20–30% of them presenting with hypertrophic obstructive cardiomyopathy (HOCM) due to left ventricle outflow tract obstruction. This is an important cause of sudden cardiac death. Endocardial radiofrequency ablation of septal hypertrophy (ERASH) might be an attractive treatment for HOCM, particularly in patients who do not respond to transcoronary alcohol septal ablation (TASA).Aim: To describe technical aspects related to the procedure and anesthetic management of an ERASH case.Case report: A 64-year-old woman with HOCM was scheduled for ERASH. She had worsening of dyspnea on exertion and generalized fatigue for the previous weeks after previous surgical myomectomy about 6 months ago. The anatomy was unfavorable for TASA and the patient was not willing to undergo another surgery. Preoperative transthoracic echocardiography (TTE) showed asymmetric mid-septal hypertrophy, systolic anterior motion with septal contact and left ventricular outflow tract maximum gradient of 68 mmHg at rest and 105 mmHg after the Valsalva maneuver. General anesthesia was performed. Pulse pressure variation, echocardiography parameters and passive leg raising test where used to guide fluid therapy. At the end of the procedure, analgesia was provided together with prophylaxis of nausea and vomiting. Extubation was uneventful and the patient was transported to the intensive care unit eupneic and hemodynamically stable. On the fourth postoperative day, TTE showed septal  hypocontractility and maximum gradient reduction of 33% at rest (68 mmHg to 45 mmHg) and 31% after the Valsalva maneuver (105 mmHg to 73 mmHg). The patient was discharged from hospital at the sixth postoperative day. One month later, she reported progressive improvement of symptoms and expressed satisfaction with the results.Conclusion: Better understanding of the pathophysiology and natural history of HCM has enabled earlier diagnosis, as well as a more adequate therapeutic approach. Anesthesiologists should be aware of the pathophysiology of HOCM and must be prepared to anticipate the hemodynamic changes and cardiovascular instability that such patients may show perioperatively. ERASH is a promising therapeutic modality increasingly used for HOCM and anesthesiologists should become more familiar with it

Integrated and dynamic energy modelling of a regional system: a cost-optimized approach in the deep decarbonisation of the Province of Trento (Italy)

Since the Kyoto Protocol (1997), the European Union has fought against climate change adopting European, national and regional policies to decarbonise the economy. Moreover, the Paris Agreement (2015) calls 2050 solutions between -80% and -100% of greenhouse gas emissions compared with 1990. Regions have an important role in curbing CO2 emissions, and tailor-made strategies considering local energy demands, savings potentials and renewables must be elaborated factoring in the social and economic context. An “optimized smart energy system” approach is proposed, considering: (I) integration of electricity, thermal and transport sectors, (II) hourly variability of productions and demands, (III) coupling the EnergyPLAN software, to develop integrated and dynamic scenarios, with a multi-objective evolutionary algorithm, to identify solutions optimized both in terms of CO2 emissions and costs, including decision variables for all the three energy sectors simultaneously. The methodology is tested at the regional scale for the Province of Trento (Italy) analyzing a total of 30,000 scenarios. Compared to the Baseline 2016, it is identified: (I) the strategic role of sector coupling among large hydroelectric production and electrification of thermal and transport demands (heat pumps, electric mobility), (II) slight increases in total annual cost, +14% for a -90% of CO2 emissions in 205