550 research outputs found
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
The reintroduction of Castor fiber in Piedmont (Italy): An integrated SWOT-spatial multicriteria based approach for the analysis of suitability scenarios
The Castor fiber or Eurasian beaver can change its habitat by building dams and creating ponds. For this reason, Castor fiber is known as an “ecosystem engineer” for aquatic and riparian environments. Despite its ecological importance, at the beginning of the 20th century the population was reduced to only 1200 beavers in Europe and Asia, due to uncontrolled hunting. Recently, some reintroductions and translocations have partly re-established the population. In Italy, however, the beaver disappeared in the 16th century and no action has been taken despite the recommendation of the Council of Europe to perform a feasibility study. This research evaluates beaver reintroduction and identifies suitable areas in Italy and, in particular, in the Piedmont region. In order to achieve this, a SWOT analysis combined with a Spatial Multicriteria Analysis was performed. Firstly, the zoological and ethological aspects concerning this rodent were studied, as well as the historical reasons that led to its disappearance in Italy and near extinction in Eurasia. Secondly, Strengths, Weaknesses, Opportunities and Threats (SWOT) of the territory were identified for beaver reintroduction. The SWOT analysis was implemented, as the starting point for the spatial multicriteria analysis. Thirdly, the Multicriteria Spatial Decision Support System (MC-SDSS) was structured into two criteria, i.e. Potentials and Criticalities, representing the spatialization of strengths and weaknesses. The final result of the MC-SDSS is a map showing suitable areas for beaver reintroduction in Piedmont. This map is the weighted sum of the maps of criticalities and potentialities, performed through a set of GIS operations and weighted through a pairwise comparison of criteria by experts. The analysis was conducted for the Piedmont region, but the integrated approach and the set of criteria can also be applied in other regions. Moreover, this mixed-method approach takes into account the characteristics necessary for the choice of suitable beaver habitats and also includes economic and social aspects. Therefore, it is an improvement on the Habitat Suitability Index (HIS), generally used in reintroductions. The aspects considered in the analysis are fundamental for the future development of a shared action plan, which considers both technical and social motivations and acts for the long-term on a wide area
Preliminary comparative serological evaluation of Histamine H2 receptors in dogs with an acute onset of vomiting treated with Ranitidine and healthy dogs
Groundwater redox conditions and conductivity in a contaminant plume from geoelectrical investigations
International audienceAccurate mapping of the electrical conductivity and of the redox potential of the groundwater is important in delineating the shape of a contaminant plume. A map of redox potential in an aquifer is indicative of biodegradation of organic matter and of concentrations of redox-active components; a map of electrical conductivity provides information on the mineralisation of the groundwater. Both maps can be used to optimise the position of pumping wells for remediation. The self-potential method (SP) and electrical resistivity tomography (ERT) have been applied to the contaminant plume associated with the Entressen landfill in south-east France. The self-potential depends on groundwater flow (electrokinetic contribution) and redox conditions ("electro-redox" contribution). Using the variation of the piezometric head in the aquifer, the electrokinetic contribution is removed from the SP signals. A good linear correlation (R2=0.85) is obtained between the residual SP data and the redox potential values measured in monitoring wells. This relationship is used to draw a redox potential map of the overall contaminated site. The electrical conductivity of the subsoil is obtained from 3D-ERT analysis. A good linear correlation (R2=0.91) is observed between the electrical conductivity of the aquifer determined from the 3D-ERT image and the conductivity of the groundwater measured in boreholes. This indicates that the formation factor is nearly homogeneous in the shallow aquifer at the scale of the ERT. From this correlation, a map of the pore water conductivity of the aquifer is obtained. Keywords: self-potential, redox potential, electrical resistivity tomography, fluid conductivity, contaminant plum
Land-use history and topographic gradients as driving factors of subalpine Larix decidua forests
none6restrictedMatteo Garbarino;Emanuele Lingua;Peter J. Weisberg;Alessandra Bottero;Fabio Meloni;Renzo MottaMatteo, Garbarino; Lingua, Emanuele; Peter J., Weisberg; Alessandra, Bottero; Fabio, Meloni; Renzo, Mott
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
Nueva técnica de microscopía electrónica de barrido para el estudio de Coccoidea (Insecta: Hemiptera)
Se presenta un protocolo para preparar material de Coccoidea (Insecta: Hemiptera) para realizar observaciones con microscopía electrónica de barrido. Esta técnica consiste en muestras conservadas en alcohol 96°, limpiadas con xilol y acetona y llevadas directamente a la etapa de hidratación y una posterior deshidratación, en alcohol, omitiendo la fi jación en formaldehído gluteraldehído y la posfijación en tetróxido de osmio. Se destaca la importancia de la limpieza del material y la correcta realización de punto crítico, en la etapa de desecación.
A new protocol to prepare material of Coccoidea (Insecta: Hemiptera) for observation with scanning electron microscopy is presented. This technique consists of cleaning samples (stored in 96% alcohol) with acetone and xylene, taking them directly to the hydration step, and subsequently dehydrating them in alcohol. Fixation in glutaraldehyde and post-fixation in osmium tetroxide are omitted. The cleaning of the samples and the correct critical point dryer are very important
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