A system dynamics model and analytic network process: An integrated approach to investigate urban resilience

During the last decade, the concept of urban resilience has been increasingly implemented in urban planning, with the main aim to design urban development strategies. Urban resilience is a multi-dimensional and dynamic concept. When applied to urban planning, it consists of studying cities as complex socio-economic systems. Municipalities are currently working to undertake appropriate actions to enrich the resilience of cities. Moreover, several difficulties concern the evaluation of the impacts over time of the strategies designed to enhance urban resilience. The present paper proposes an integrated approach based on the System Dynamics Model (SDM) and the Analytic Network Process (ANP). The objective of this research is to describe the method and to illustrate its application to the area called Basse di Stura, located in the city of Turin, Italy. The method is applied to evaluate the possible impacts of two different urban scenarios in terms of the change of urban resilience performance over time. The final result is represented by an index that describes urban resilience performance

Buildings energy performance and real estate market value: An application of the spatial auto regressive (SAR) model

The paper explores the role of the buildings energy performance in the definition of the real estate market value, taking in consideration the presence of spatial auto-correlation. At this regard, it is necessary to put in evidence that a great heterogeneity exists on the Italian territory with reference to buildings ener-gy performance; for this reason, being able to identify a class of most performing estimation models, suitable to separate the spatial effects from the influence of the building components - including the energy rating - on the value, seems to be an interesting goal. In particular, this work illustrates an experiment based on the Spatial Auto Regressive (SAR) model implemented on a sample of residential units located in the city of Turin and represents a first step of a more wide research program

An axisymmetric time-domain spectral-element method for full-wave simulations: Application to ocean acoustics

The numerical simulation of acoustic waves in complex 3D media is a key topic in many branches of science, from exploration geophysics to non-destructive testing and medical imaging. With the drastic increase in computing capabilities this field has dramatically grown in the last twenty years. However many 3D computations, especially at high frequency and/or long range, are still far beyond current reach and force researchers to resort to approximations, for example by working in 2D (plane strain) or by using a paraxial approximation. This article presents and validates a numerical technique based on an axisymmetric formulation of a spectral finite-element method in the time domain for heterogeneous fluid-solid media. Taking advantage of axisymmetry enables the study of relevant 3D configurations at a very moderate computational cost. The axisymmetric spectral-element formulation is first introduced, and validation tests are then performed. A typical application of interest in ocean acoustics showing upslope propagation above a dipping viscoelastic ocean bottom is then presented. The method correctly models backscattered waves and explains the transmission losses discrepancies pointed out in Jensen et al. (2007). Finally, a realistic application to a double seamount problem is considered.Comment: Added a reference, and fixed a typo (cylindrical versus spherical

A methodological framework for the economic assessment of ict-tools for occupants’ engagement

The concept of smartness in building dates to the 1970s, but, in face of the breakthrough technological developments, a new notion of smart building is currently recognized. We talk about ambient intelligence, referring to a building which is responsive to the needs of the occupants and of the energy system. An ambient-intelligent building is human-centric; new services and interfaces are provided to the buildings occupants to learn and set their preferences, with a positive impact on their comfort level and satisfaction with the indoor environmental quality. ICT and IoT are part of the enabling technologies to exploit the potentials of smart buildings, by unlocking the capability of buildings to interact with the system they belong to. To bolster the diffusion of new technologies, methodologies to get quantitative results proving their effectiveness should be provided. In this paper the application of a well-established economic evaluation tool, the so-called Cost-Benefit Analysis, to the case of the deployment of new ICT-tools for occupants’ engagement is presented. The methodology is adopted within the H2020 Mobistyle project, where two levels of the evaluation are identified: the whole project level and the single demo case one. The purpose of the methodology is to assess the effectiveness of the adoption of the ICT-tools in producing economic value in terms of benefits for the occupants and the society. Some preliminary results of its application to the Italian case study are also presented, showing a positive socio-economic balance since the beginning of the deployment

Value-Distributional Model-Based Reinforcement Learning

Quantifying uncertainty about a policy's long-term performance is important to solve sequential decision-making tasks. We study the problem from a model-based Bayesian reinforcement learning perspective, where the goal is to learn the posterior distribution over value functions induced by parameter (epistemic) uncertainty of the Markov decision process. Previous work restricts the analysis to a few moments of the distribution over values or imposes a particular distribution shape, e.g., Gaussians. Inspired by distributional reinforcement learning, we introduce a Bellman operator whose fixed-point is the value distribution function. Based on our theory, we propose Epistemic Quantile-Regression (EQR), a model-based algorithm that learns a value distribution function that can be used for policy optimization. Evaluation across several continuous-control tasks shows performance benefits with respect to established model-based and model-free algorithms

Information-Theoretic Safe Exploration with Gaussian Processes

We consider a sequential decision making task where we are not allowed to evaluate parameters that violate an a priori unknown (safety) constraint. A common approach is to place a Gaussian process prior on the unknown constraint and allow evaluations only in regions that are safe with high probability. Most current methods rely on a discretization of the domain and cannot be directly extended to the continuous case. Moreover, the way in which they exploit regularity assumptions about the constraint introduces an additional critical hyperparameter. In this paper, we propose an information-theoretic safe exploration criterion that directly exploits the GP posterior to identify the most informative safe parameters to evaluate. Our approach is naturally applicable to continuous domains and does not require additional hyperparameters. We theoretically analyze the method and show that we do not violate the safety constraint with high probability and that we explore by learning about the constraint up to arbitrary precision. Empirical evaluations demonstrate improved data-efficiency and scalability.Comment: Submitted to NeurIPS 202

Bordetella bronchiseptica aislada en paciente con Fibrosis Quística

Presentamos el caso de una paciente de 15 años con Fibrosis Quística (FQ) en la cual, en dos oportunidades y con un intervalo de 2 años, se aisló Bordetella bronchiseptica con idéntico perfil genético estudiado por electroforesis de campo pulsado. El mecanismo lesional de B. bronchiseptica en el árbol bronquial de pacientes con FQ no está claramente establecido, pero la habilidad de esta bacteria para inhibir la función de los leucocitos y su capacidad de adherirse a las células del epitelio bronquial explicaría su capacidad infectiva y su persistencia en el tracto respiratorio.We are reporting the case of a 15 year-old girl with Cystic Fibrosis in whom Bordetella bronchiseptica was isolated twice, two years apart. The germ showed identical genetic profile when studied by pulsed-field gene electrophoresis. The ways Bordetella bronchiseptica causes damage to the lower respiratory tract remains unsettled. The capacity of this germ to inhibit leukocyte function and its adherence to bronchial epithelial cells could explain its pathogenicity and persistence