Solution of the Navier-Stokes equations for a driven cavity

The flow field in a lid driven cavity is determined by integration of the incompressible Navier-Stokes equations. The numerical integration is accomplished via an operator splitting method known as the theta-scheme. This splitting separates the problem into the solution of a quasi-stokes problem and a nonlinear convection problem. Some details of solution methods used for the two subproblems and results obtained for the driven cavity are described. The schemes developed for the quasi-Stokes problem are more advanced at this stage than those for the nonlinear problem. However, the approaches used for both parts are outlined. As a model problem, a two dimensional square cavity with sides of unit length and a lid moving with unit velocity from left to right is considered. The Navier-Stokes equations are discretized in space on a uniform staggered or MAC mesh. The time discretization is accomplished via the theta-scheme

Application of vegetation index time series to value fire effect on primary production in a Southern European rare wetland

Fire disturbance is an intrinsic component of the Mediterranean biome playing an important role in ecosystem dynamics and processes. However, frequent and severe anthropogenic wildfires can be detrimental to natural ecosystems, particularly in small natural protected areas, where they may hamper the flow of ecosystem services (ES). While post-fire dynamics of individual ES are heavily context-dependent, the primary productivity of the ecosystem can be regarded as a generic driver of several provisioning and regulating ES, as it represents the amount of energy available to plants for storage, growth, and reproduction, which drives future ecosystem structure and functions. The aim of this study was to evaluate the effect of anthropogenic wildfire on the primary productivity of a rare wetland ecosystem in the Natura 2000 site \u201cTorre Guaceto\u201d in Southern Europe. Productivity was estimated by calculating a 15-year time series of vegetation indices (EVI and NDWI)from remotely sensed MODIS imagery. Our results in terms of PP trends may be relevant to assess the change in ecosystems services provided by wetlands. Interactions between wildfire, ecosystem productivity and climate were then analyzed. During the selected period, climate did not play a significant effect on primary productivity, which was mainly driven by post-fire vegetation recovery. Findings of the present study demonstrate that the wildfire affecting the Natural Protected Area of Torre Guaceto in summer 2007 had a major effect on primary productivity, inducing the regeneration of Phragmites australis and the replacement of old individuals by structurally and functionally better ones

Resolvent Analysis: With or Without Eddy Viscosity?

International audienceIn this study, estimations of the spatio-temporal power cross-spectral density based on the resolvent operator are compared to those obtained by direct numerical simulation (DNS) in the turbulent plane channel flow at Re τ = 1007 by analysing separately the contribution of each temporal frequency ω. The comparison is performed for spatial scales characteristic of buffer-layer and large-scale motions. Good agreement between the resolvent-based estimates and the statistics obtained by DNS is found when the resolvent operator is based on a linear model which includes the effect of an eddy-viscosity modelling the effect of turbulent Reynolds stresses. The agreement is further improved when a colored noise matching the measures is used instead of white noise in the forcing modelling. Such a good agreement is not observed when the eddy-viscosity terms are not included in the linear model. In this case, the estimation based on the resolvent is unable to select the right peak frequency and wall-normal location of buffer-layer motions

XAI.it 2020 - Preface to the first italian workshop on explainable artificial intelligence

Artificial Intelligence systems are increasingly playing an increasingly important role in our daily lives. As their importance in our everyday lives grows, it is fundamental that the internal mechanisms that guide these algorithms are as clear as possible. It is not by chance that the recent General Data Protection Regulation (GDPR) emphasized the users’ right to explanation when people face artificial intelligence-based technologies. Unfortunately, the current research tends to go in the opposite direction, since most of the approaches try to maximize the effectiveness of the models (e.g., recommendation accuracy) at the expense of the explainability and the transparency. The main research questions which arise from this scenario is straightforward: how can we deal with such a dichotomy between the need for effective adaptive systems and the right to transparency and interpretability? Several research lines are triggered by this question: building transparent intelligent systems, analyzing the impact of opaque algorithms on final users, studying the role of explanation strategies, investigating how to provide users with more control in the behavior of intelligent systems. XAI.it, the first Italian workshop on Explainable AI, tries to address these research lines and aims to provide a forum for the Italian community to discuss problems, challenges and innovative approaches in the various sub-fields of XAI

A techno-economic approach for decision-making in metal additive manufacturing: metal extrusion versus single and multiple laser powder bed fusion

This work presents a decision-making methodology that allows the merging of quantitative and qualitative decision variables for selecting the optimal metal Additive Manufacturing (AM) technology. The approach is applied on two competing technologies in the field of metal AM industry, i.e., the metal extrusion AM process (metal FFF) and the Laser Powder Bed Fusion process (LPBF) with single and multiple lasers, which represent the benchmark solution currently on the market. A comprehensive techno-economical comparison is presented where the two processes are analysed in terms of process capabilities (quality, easiness of use, setup time, range of possible materials, etc.) and costs, considering two different production scenarios and different parts’ geometries. In the first scenario, the AM system is assumed to be dedicated to one single part production while in this second scenario, the AM system is assumed to be saturated, as devoted to producing a wide mix of part types. For each scenario, two different part types made of 17–4 PH stainless steel are considered as a reference to investigate the effect of shape complexity, part size and production times to select the best technology when metal FFF and LPBF must be considered. The first part type refers to an extrusion die, to represent typical shapes of interest in the tooling industry, while the second part type is an impeller which can be used in many different industrial sectors, ranging from oil and gas to aerospace. In order to include quantitative and qualitative criteria, a decision-making model based on Analytic Hierarchy Process (AHP) is proposed as the enabler tool for decision making. The proposed approach allows to determine the most effective solution depending on the different production configurations and part types and can be used as a guideline and extended to include other technologies in the field of metal AM. On the other side, the critical discussion of the criteria selected, and the results achieved allow to highlight the pros and cons of the competing technologies, thus defining the existing limits to define directions for future research

Acute Dacryocystitis with Empyema of the Lacrimal Sac: Is Immediate Endoscopic Dacryocystorhinostomy Justified?

Objectives. To evaluate the efficacy of endoscopic dacryocystorhinostomy (Endo-DCR) in the treatment of acute dacryocystitis with lacrimal sac empyema (ADLSE). Design. Case series with chart review. Setting. Academic tertiary center. Patients. The study included 26 consecutive patients who underwent Endo-DCR for ADLSE between August 2005 and December 2013. Main Outcome Measures. The success of the procedure was defined as complete complaint relief and DCR patency. Data on the time from referral to surgery, postoperative complications, and revision surgery are also reported. Results. The present patient series included 4 males (15.4%) and 22 females (84.6%) (mean age, 66 years). The mean time between referral and surgery was 0.88 days and the mean follow-up time was 29 months. All patients showed immediate relief from symptoms, with no ADLSE recurrences. Complete success was achieved in 25 (96.2%) cases; the only failure was in a patient who had previously undergone radioiodine treatment. In this case, revision Endo-DCR was not successful. The only perioperative complication (3.8%) was epistaxis in a patient who required revision surgery under general anesthesia. The definitive success rate was 96.2% after primary and revision surgery. Conclusions. Endo-DCR enables rapid resolution of ADLSE with a very high success rate. Immediate surgery may reduce the risk of skin fistulization and/or orbital complications. DCR shrinkage and lacrimal obstruction are unlikely with Endo-DCR since the procedure is performed on an enlarged sac. The main advantage of Endo-DCR, compared with external DCR, is the absence of a skin incision in an inflamed and infected field

Exploring the effects of natural language justifications in food recommender systems

Users of food recommender systems typically prefer popular recipes, which tend to be unhealthy. To encourage users to select healthier recommendations by making more informed food decisions, we introduce a methodology to generate and present a natural language justification that emphasizes the nutritional content, or health risks and benefits of recommended recipes. We designed a framework that takes a user and two food recommendations as input and produces an automatically generated natural language justification as output, which is based on the user's characteristics and the recipes' features. In doing so, we implemented and evaluated eight different justification strategies through two different justification styles (e.g., comparing each recipe's food features) in an online user study (N = 503). We compared user food choices for two personalized recommendation approaches, popularity-based vs our health-aware algorithm, and evaluated the impact of presenting natural language justifications. We showed that comparative justifications styles are effective in supporting choices for our healthy-aware recommendations, confirming the impact of our methodology on food choices

Exploring the effects of natural language justifications in food recommender systems

Users of food recommender systems typically prefer popular recipes, which tend to be unhealthy. To encourage users to select healthier recommendations by making more informed food decisions, we introduce a methodology to generate and present a natural language justification that emphasizes the nutritional content, or health risks and benefits of recommended recipes. We designed a framework that takes a user and two food recommendations as input and produces an automatically generated natural language justification as output, which is based on the user’s characteristics and the recipes’ features. In doing so, we implemented and evaluated eight different justification strategies through two different justification styles (e.g., comparing each recipe’s food features) in an online user study (N = 503). We compared user food choices for two personalized recommendation approaches, popularity-based vs our health-aware algorithm, and evaluated the impact of presenting natural language justifications. We showed that comparative justifications styles are effective in supporting choices for our healthy-aware recommendations, confirming the impact of our methodology on food choices

A virtual customer assistant for the wealth management domain in the UWMP project

The Universal Wealth Management Platform (UWMP) project has the objective of creating a new service model in the financial domain. An integral part of this service model is the creation of a new Virtual Customer Assistant, that is able to assist customers via natural language dialogues. This paper is a report of the activities performed to develop this assistant. It illustrates a general architecture of the system, and describes the most important decisions made for its implementation. It also describes the main financial operations that it is able to assist customers with. Finally, it delineates some avenues for future work

Ethical issues associated with in-hospital emergency from the medical emergency team's perspective: a national survey

Medical Emergency Teams (METs) are frequently involved in ethical issues associated to in-hospital emergencies, like decisions about end-of-life care and intensive care unit (ICU) admission. MET involvement offers both advantages and disadvantages, especially when an immediate decision must be made. We performed a survey among Italian intensivists/anesthesiologists evaluating MET's perspective on the most relevant ethical aspects faced in daily practice