Importance of CBCT in the management plan of upper canine with internal resorption

Abstract Aim Internal root resorption is a particular medical condition which requires the clinician to a treatment as early as possible to avoid complications such as excessive loss of mineralized tissues and periodontal communications. Methodology This article describes the diagnosis and treatment of a case of internal resorption of an upper canine in a patient of 21 years. The presence of pain and swelling periodontal gum showed an interest, a sign of the presence of a perforation. Result and conclusions Accurate diagnosis associated with the three-dimensional evaluation of the internal fault (CBCT examination) have allowed a conservative treatment who has allowed the recovery of the tooth

Artificial intelligence in construction asset management: a review of present status, challenges and future opportunities

The built environment is responsible for roughly 40% of global greenhouse emissions, making the sector a crucial factor for climate change and sustainability. Meanwhile, other sectors (like manufacturing) adopted Artificial Intelligence (AI) to solve complex, non-linear problems to reduce waste, inefficiency, and pollution. Therefore, many research efforts in the Architecture, Engineering, and Construction community have recently tried introducing AI into building asset management (AM) processes. Since AM encompasses a broad set of disciplines, an overview of several AI applications, current research gaps, and trends is needed. In this context, this study conducted the first state-of-the-art research on AI for building asset management. A total of 578 papers were analyzed with bibliometric tools to identify prominent institutions, topics, and journals. The quantitative analysis helped determine the most researched areas of AM and which AI techniques are applied. The areas were furtherly investigated by reading in-depth the 83 most relevant studies selected by screening the articles’ abstracts identified in the bibliometric analysis. The results reveal many applications for Energy Management, Condition assessment, Risk management, and Project management areas. Finally, the literature review identified three main trends that can be a reference point for future studies made by practitioners or researchers: Digital Twin, Generative Adversarial Networks (with synthetic images) for data augmentation, and Deep Reinforcement Learning

Gaining knowledge from big data: energy performance certificate as a source of information to decarbonize the built environment

The decarbonization strategies for the built environment that policy-makers face today from the EU mandate risk being made with incomplete or insufficient information. The consequence of this could be ineffective choices, thus slowing down the ongoing ecological transition, or their high cost, whether borne by the state or citizens. The progressive and unstoppable digitization of the built environment offers information collection and previously unthinkable management opportunities. The construction sector, traditionally lagging behind other industrial sectors, is beginning to produce large quantities of data that can be exploited thanks to the most modern techniques derived from the information technology sector. Among the most promising data sources are energy performance certificates for buildings, which provide a snapshot of the characteristics of buildings, their fabric and plant components, and design forecasts of their energy performances. Analyzing the energy performance certificates through Artificial Intelligence techniques proves the effectiveness of using big data in the construction sector. In particular, in this study, unsupervised machine learning techniques led to an in-depth knowledge of a stock of buildings approaching two hundred thousand units distributed over an almost twenty-four thousand square kilometers area in northern Italy

Ludwig's angina: a case report with a 5-year follow-up

Aim: Ludwig's angina is a rare aggressive infection, often of dental origin, characterized by a rapid spread of cellulitis in the submandibular and sublingual spaces. Ludwig's angina is potentially fatal, if it obstructs the airways and if it is not treated with appropriate antibiotic therapy. Summary: The case report describes the diagnosis and the management of a Ludwig's angina caused by an endodontic infection in a 16 years-old female patient. The infection has been caused by a decay of the second lower right molar. After hospitalization and systemic antibiotic therapy, in accordance with the patient and the parents endodontic and restorative treatments of the tooth were performed. After 3 and 5 years, the radiological examination revealed no periapical lesions around right lower second molar and the presence of lamina dura. Key learning points: This aggressive infection may often be undervalued and this may cause dangerous consequences to the patient's life. The infection can be prevented by periodic dental care and interventions, which can avoid odontogenic infections. In the case of Ludwig's angina, early diagnosis is fundamental to save the patient's life. After the initial antibiotic therapy and once the life of the patient is no longer at risk, an appropriate endodontic therapy can be considered a valid therapy for this disease. Riassunto: Obiettivi: L'angina di Ludwig è un'infezione aggressiva, spesso di origine odontogena, caratterizzata da una raccolta cellulitica a rapida evoluzione che coinvolge gli spazi sotto-mandibolare e sotto-linguale. Essa può ostruire le vie respiratorie ed essere potenzialmente fatale se non tempestivamente trattata con cure antibiotiche appropriate. Riassunto: In questo articolo viene descritto un caso di diagnosi e trattamento di un'angina di Ludwig causata da un'infezione odontogena in una ragazza di 16 anni. L'infezione é stata causata da una carie a carico del secondo molare inferiore di destra. Dopo il ricovero ospedaliero ed una terapia antibiotica sistemica parenterale, con il consenso dei genitori abbiamo è stata eseguita una terapia endodontica e la successiva ricostruzione con materiali adesivi dell'elemento dentario in questione. Dopo 3 e 5 anni gli esami radiografici mostrano assenza di lesioni periapicali e la presenza della lamina dura. Punti chiave di apprendimento: Questa infezione aggressiva è spesso sottovalutata e ciò può causare conseguenze gravi per la vita del paziente. Tali infezioni possono essere prevenute con controlli periodici del cavo orale. In caso di angina di Ludwig una diagnosi tempestiva è fondamentale per salvare la vita del paziente. Dopo l'iniziale terapia antibiotica ed aver messo in sicurezza la salute generale del paziente, la terapia endodontica può essere considerata una valida alternativa per questa patologia. Keywords: Ludwig's angina, Endodontic therapy, Endodontic infection, CBCT, Management infection, Parole chiave: Angina di Ludwig, Terapia endodontica, Infezione endodontica, CBCT, Gestione dell'infezion

Data driven economic scenarios for retrofitting residential buildings in a northern Italian region

European directives and strategies, such as the 'European Green Deal' and the 'Ren- ovation Wave', point out the importance of the building sector in achieving the climate goals set by the European Union for 2050. However, a higher renovation rate for the existing buildings is required to achieve these goals. Many barriers prevent the renovation rate from growing. Regarding financial barriers, the long payback times of renovation interventions and the high risk perceived by the potential investors make the renovation rate remain low. Based on data from energy performance certificates, this research proposes a data-driven method to create economic retrofit scenarios for residential buildings using Artificial Intelligence techniques and Monte Carlo simulations. Namely, energy savings have been predicted using an Artificial Neural Network on clusters of residential buildings and the Life Cycle Costs forecasted by Monte Carlo simulations taking into account the uncertainty in many of the inputs. Results obtained by applying the method to a region in northern Italy illustrate two scenarios for the energy retrofit of the built environment, one assuming a payback time of fifteen years and the other of twenty- five years. In both cases, the maximum allowable investment, which varies according to the specific characteristics of the buildings, is much lower than the retrofit costs recorded in the same area in recent years

Data-Driven Process Mining Framework for Risk Management in Construction Projects

Construction Projects are exposed to numerous risks due to their complex and uncertain nature, threatening the realization of the project objectives. However, Risk Management (RM) is a less efficient realm in the industry than other knowledge areas given the manual and time-consuming nature of its processes and reliance on experience-based subjective judgments. This research proposes a Process Mining-based framework for detecting, monitoring, and analysing risks, improving the RM processes using evidence-based event logs, such as Risk Registers and Change-Logs within previous projects' documents. Process Mining (PM) is a data- driven methodology, well established in other industries, that benefits from Artificial Intelligence(AI) to identify trends and complex patterns among event logs. It performs well while intaking large amounts of data and predicting future outputs based on historical data. Therefore, this research proposes a Bayesian Network (BN)-based Process Mining framework for graphical representation of the RM processes, intaking the conditional dependence structure between Risk variables, and continuous and automated risk identification and management. A systematic literature review on RM, PM, and AI forms the framework theoretical basis and delineates the integration areas for practical implementation. The proposed framework is applied to a small database of 20 projects as the case study, the scope of which can be tailored to the enterprise requirements. It contributes to creating a holistic theoretical foundation and practical workflow applicable to construction projects and filling the knowledge gap in inefficient and discrete conventional RM methods, which ignore the interdependencies between risk variables and assess each risk isolated

Streamlined management of the built environment: the district and the building logbook as risk prevention tools

Management of information related to the real properties is a key topic both in private and public sector. In the Italian context, can be spotted an overall lack of organisation of the information concerning the real estate assets, from the building scale, to the neighbourhood, until the city and the territory. Moreover, management of the urban environment is characterised by the presence of different players asking for common needs in management and use of data. This research aims at proposing the Building Logbook and the District Logbook as tools for collection, organisation and management of information, in a perspective of streamlined real estate management process. Moreover, the Logbooks can be conceived as tools for risk management. They should be exploited especially in technical management phase of assets, as well as in the verification of compliance with laws, authorisations and licenses, since these issues often bear to disputes between public and private players. Often disputes concern that areas where the competences and responsibilities among different players are not clear (connections to system, property boundaries, licenses, occupation of public land etc.). In this situations, information management assumes a key role, since it could be a powerful mean to clarify responsibilities among players. Therefore, the scope of the research concerns the investigation on the relationships and related information flows among stakeholders in the real estate field. Altogether, it can be stated that the logbooks can streamline processes in the use phase of assets, despite they could be intended as rigid control tools. Through this paper these issues will deepened and clarified. The paper concludes with some considerations concerning the possible integration of the Logbooks in a digital environment, following the BIM approach

Dynamic Facility Condition Index calculation for asset management

Aim of this research is to investigate the possibility of dynamically computing the Facility Condition Index (FCI) using a database of maintenance operations and costs of fabric and services components. This would lead to an instrument able to support decision making during asset and portfolio management because FCI is widely considered a good indicator for monitoring assets and portfolios conditions; so being able to efficiently calculate and update it is fundamental for a proper asset management. There are many ways to benchmark assets condition, but most of them are qualitative and lead to ratings in percentage, that need to be further elaborated to be connected to annual OM&R costs. The FCI can be considered an economic rating, based on money paid for maintenance, repair and replacement performed over the current asset value. The objective is to make an appraisal of the maintenance costs in a dynamic way, so to be able to examine multiple scenarios and make forecasts; the facility value comes from market appraisals with some coefficient applied, if need be. This calculation procedure, together with a maintenance operations and costs database developed by the authors (either forecasted or real costs), can be used by asset managers to support decisions about maintenance and repair actions to be undertaken. This paper shows preliminary results of this research, with the help of a case study. Further correlations should be investigated, even if this calculation procedure leads to an effective management. The calculation procedure and the database organization are an original work of the authors, as well as the case study used to show the results. In addition to this, connections among the indicators provided and BIM (Building Information Modelling) models are analyzed

A Multi-criteria Framework for Decision Process in Retrofit Optioneering through Interactive Data Flow

Aim of this research is to deliver a system of procedures and instruments that allows comparing different scenarios of restoration and retrofit of existing buildings applicable each time a relevant decision about the asset has to be made. The system developed takes advantages of Building Information Modeling (BIM) and Analytical Hierarchy Process (AHP), thus to focus on main clients’ needs. Decisions about real estate assets are frequently made by managers with incomplete and scattered data, not sufficient to fully support the decision making process. Using a BIM model as a central repository of information could strongly support to compare objectively different scenarios and consequently to decide the application of a multi-criteria matrix involving management, energy, economic and social issues. BIM and BEM (Building Energy Modelling) techniques have a wide potential and analysis capabilities; however, they are often adopted without an integrated framework, causing missing performances and costs overrun. The result is a system enabling to analyze the asset, to produce BIM and BEM models ready to include life cycle data, to evaluate feasible alternatives and scenarios and to extract relevant performance indicators for decision makers’ support. An existing office building in Milan representing an awkward field for intervention is the case study for the system application. While the tools and software adopted are commonly used, the system of procedures developed by the authors can be considered as an ensemble of workflows otherwise typically used independently. Using them together enhance the decision process providing data on which to set up a strategic plan of the refurbishment considering costs, continuity in occupancy and energy efficiency