77 research outputs found
Empathy between Art and Design
No full textThis short essay delineates the art contest in which the notion of empathy developed between the late 19th and the early 20th century. Explores its meaning as the condition that makes intersubjectivity possible in Husserlian Phenomenology, especially in Edith Stein’s interpretation. It provides clues to understand the reasons that brought design culture focusing on empathy from the late 1990s onward. The increase of the participatory approach in design processes puts intersubjectivity – and therefore empathy – at the centre of any design practice.
Since Alice Devecchi, the author of the book in which the essay appears, focuses on empathy or, more precisely, on designing the empathic experience, the text provides comments and clues about the contest, the approach and the outcomes of her work – primarily focusing on the relevance of the arts as a means to increase design knowledge, an approach to research that Devecchi shares with the author, who also was the supervisor of her PhD thesis
Gli investimenti non finanziari nel private banking: scelte strategiche, aspetti tecnico-valutativi e modalità di customer relationship management.
No full textL'obiettivo della ricerca è evidenziare se l'investimento in beni non finanziari è preso in considerazione dalle private banks operanti in Italia nella costruzione dei portafogli dei loro clienti facoltosi, se nel processo di ottimizzazione siano seguite le logiche della modern portfolio theory e quali modalità vengono adottate nella fase di presentazione delle performance. si procede quindi ad esaminare gli investimenti in oro, in arte, in diamanti, in vino e in immobili per verificarne gli impatti sulla rischiosità e sulle performance di portafoglio.The goal of this thesis is to verify if private banks that operate in Italy use goods as investment for diversifying HNW or U-HNW individuals portfolio, if they take in consideration the modern portfolio theory for asset allocation and how performances are presented to investors. So it analyses the investment as gold, real estate, art, diamond and wine to achieve the impact of them on portfolio risk and performance
Empathy for resilience
No full textThe essay stresses the potential value of empathy in designing strategies for resilience. We question the traditional idea of empathy as an individual skill addressed to understand the other, in support of a conceptualization closer to the phenomenological interpretation, focused on the relational dynamics at stake in human encounters. The paper reconsiders empathy as an experience valuable for strengthening a resilient attitude within collaborative projects. A case study will be featured, i.e. Design in The Middle, an ongoing project that gathers designers, architects and social activists from the Middle East/Euro-Med regions with the aim of generating design proposals to address challenges relevant to the Middle East. As participants come from very different cultural, political and religious backgrounds, their cooperation is a central and critical issue, which might benefit from contextual and relational “rules” enabling empathic experiences. In the context of the first Design in The Middle workshop (2017), some strategies have proven to be crucial in enabling effective communication over complex design issues. These strategies will be analysed according to a methodology developed in a previous research carried out by the author(s) (Devecchi, 2018) about the role of empathy in collaborative processes. Assuming that a resilient society preserves and supports cultural diversity, Design in the Middle stands as an example of collaborative design practice aimed at creating a more resilient future for these regions in which the coexistence of diverse cultural, religious and political positions is a substantial matter of concern
Rilevare un’opera cinetico - programmata per gestire le sue trasformazioni
No full textThe present contribution addresses the challenges raised by loaning, maintaining
and restoring Ambiente - Strutturazione a parametri virtuali, by Gabriele Devecchi.
The immersive, kinetic and programmed environment, permanently showcased at
Museo del ‘900 in Milan, consists of a blank trapezoidal box in which users are
invited to enter and experiment the continuous variation of spatial references,
drawn by moving lights hidden behind the side walls.
A kinetic-programmed artwork is by its very nature a structure in variation.
Therefore it needs strategies for managing its change’s path, be it of the
conservation status or of the context in which it is exhibited. It's worth to
investigate the way in which the environment functions, its mechanisms and the
relation established with user and context. Hence, the contribution focusses on the
environment’s structure, the relationships with the museum context and the
management of its change when asked for loaning.
As a kinetic-programmed environment, Ambiente - Strutturazione a parametri
virtuali is made up of several parts – functional and aesthetic – that, when in the
need for a re-location, may change according to the spatial context, indeed with
due regard for the final effect pursued by the author. In this respect, one issue is
defining uniquely which of the parts the work’s identity consists of; another, is
understanding how they should be mantained, restored, replaced or even
reproduced and who’s to guarantee the correct operation if it needs to be “moved”.
Out of these premises comes the need to document the kinetic mechanism
connected to the lights, and to describe how the environment works, with the aim
of designing guidelines in support of the stakeholders involved in managing its
conservation and potential re-location, for instance in case of loaning.
A standard workflow in approaching the task of elaborating a complete dossier
about the artwork starts with planning the survey and measuring of its parts.
The contribution is intended to be a preparatory reflection for an informed
management of such particular cases, in which issues about the proper definition of
the work’s identity wave into the challenges posed by its use and the correct
conservation plan
Designing the empathic experience. A workshop
No full textThe paper reports a workshop held by the author at the University of Aveiro. Part of an ongoing PhD research focused on the possibility of designing the empathic experience, the workshop Design for Empathy involved 4 PhD students in Design, with research interests in design for social innovation, and a professor of UX design. The participants were asked to assess and review a list of ‘enablers’ of the empathic experience, previously identified by the author among some case studies presented in the workshop along with the relevant ‘enablers’. The ‘enablers’ are intended as conditions that make the empathic experience happen within relational situations, The research stems from the assumption that these conditions can be designed to some extent. In the present paper the workshop Design for Empathy will be reported providing an insight in its structure and development, as well as some of the results achieved. Nevertheless, being the workshop part of an ongoing research, the argumentation leaves room to a wide range of conclusions that will not be stressed here
Landscape and Agriculture 4.0: A Deep Farm in Italy in the underground of a Public Historical Garden
No full textEach landscape is the result of an encounter with the culture of a community and the physical features of a territory. The conservation of the historical, artistic, and cultural heritage
represents a priority for any society that wishes to draw on references for its civil progress. The aim of the present research is to combine the richness of the historical–cultural heritage with innovative forms of agriculture. It focuses on the recovery, in productive terms, of an air-raid shelter used during the SecondWorldWar, located in the center of Varese beneath the Estensi Historical Gardens. The project involves the construction of an underground Vertical Farm (Deep Farm) with the aim of
restoring a place of memory, making it more accessible than it is today, and raising public awareness about a new cultivation model. A Deep Farm was designed with a cultivation area in the middle, an educational room, and two hygiene rooms, one at each end of the tunnel. A Vertical Farm was conceived to be shared with local stakeholders to produce vegetables and to foresee an innovative reality in the field of education and tourism. This project has the ambition of representing a model
that could be used for similar Italian realities and enhancing meeting places between landscape and modern culture diversities
Exploring regional inequities in food safety practices and food security in Italy: A cross-sectional study
No full textObjective: This study examined regional disparities in food security and food safety knowledge and behavior among Italian adults. Methods: Between January and June 2024, we conducted a cross-sectional anonymous online survey targeting Italian residents aged ≥18. The sample size was calculated a priori assuming a 50% prevalence, 95% confidence, and 3% margin of error, yielding a target of 1067 participants. Validated Italian versions of the Food Security Survey Module (It-FSSM) and the Food Safety Knowledge and Behavior Questionnaire (It-FSKB) were employed to assess participants' knowledge and behaviors. Sociodemographic data, including age, sex, body mass index (BMI), educational level, physical activity, smoking habits, and food apps usage, were collected. Multinomial logistic regression-adjusted for age, sex, BMI, and educational level-was used to evaluate regional differences. Results: Among 1752 participants (70.4% women; mean age: 36.01 ± 13.84 y), those in the South area and Islands were significantly less likely to report high food safety knowledge (relative risk ratio [RRR] = 0.66; 95% confidence interval [CI]: 0.54-0.82; P = 0.000) and high food safety behaviors (RRR = 0.64; 95% CI: 0.52-0.79; P < 0.001), and more likely to experience moderate food insecurity (RRR = 1.64; 95% CI: 1.00-2.69; P = 0.048) compared to participants to the North. Participants in the Center were over twice likely than those in the North to report high food security versus very low (RRR = 2.72; 95% CI: 1.15-6.43; P = 0.023) and were also 30% less likely to use food delivery apps rarely rather than not at all (RRR = 0.70; 95% CI: 0.50-0.97; P = 0.034). Conclusions: This study highlights significant regional disparities, with the South area and Islands facing the greatest challenges. These findings provide evidence to guide targeted public health interventions and policies promoting food safety and security across Italy
Optofluidic device for the improvement of SNR in spontaneous Raman spectroscopy of flowing samples
No full textLAUREA MAGISTRALEI dispositivi lab–on–chip (LoC) rappresentano una promettente tecnologia di identificazione di specie chimiche per diversi ambiti scientifici, dalla diagnostica medica alle analisi ambientali. I vantaggi degli LoC, come il consumo ridotto di campione, l’elevata portabilità e la brevità delle analisi, discendono della loro natura miniaturizzata. La microfluidica, ovvero la manipolazione di piccole quantità di fluido con strutture micrometriche, permette l’integrazione su chip delle funzionalità necessarie per un’analisi chimica. Gli LoC optofluidici sfruttano la sinergia tra microfluidica e fotonica, grazie alla quale si distinguono, tra gli altri LoC, per robustezza e sensibilità di rilevazione. Tra le tecniche di analisi ottica, la spettroscopia Raman ha acquisito popolarità poiché consente l’identificazione non invasiva e label–free di specie chimiche, basandosi sul segnale diffuso anelasticamente da un campione irradiato con una sorgente di luce coerente. L’unione tra microfluidica e spettroscopia Raman è potenzialmente di estrema utilità. Tuttavia, la debolezza del segnale Raman e gli esigui volumi di campione in un sistema microfluidico, rendono necessario un miglioramento della sensibilità dei sistemi LoC Raman. Per evitare l’uso di setup ottici ingombranti e costosi, una possibile alternativa prevede di eseguire la spettroscopia Raman su chip tramite fibre ottiche. Ciò migliora la portabilità, riduce i costi e contribuisce a limitare il rumore generato durante la misura. In questo lavoro è presentato un LoC optofluidico in vetro, che consente di eseguire la spettroscopia Raman, in fibra, di campioni fluidi. La tecnica di fabbricazione adottata è la femtosecond–laser irradiation followed by chemical etching (FLICE). In primis, il funzionamento del dispositivo è caratterizzato, e successivamente è riportato un incremento di sensibilità di un fattore due, ottenuto con l’integrazione di uno specchio microottico. Il miglioramento del SNR osservato in questo lavoro spera di contribuire alla diffusione di un numero crescente di applicazioni Raman portabili, economiche ed eseguite in tempo reale.Lab–on–chip (LoC) devices have emerged as a promising technology for the detection of chemical analytes in several domains of science, ranging from medical diagnostics to environmental analysis. LoCs feature several peculiar advantages, by virtue of their miniaturized nature, such as minimal sample consumption, high portability, and reduced analysis time. Microfluidic technology, that is the manipulation of small amount of fluids via micrometric–sized structures, permits the integration on miniaturized platforms of the needed functionalities for chemical analyses. Optofluidic LoCs leverage the synergetic combination of microfluidics and photonics. Such devices have stood out, among miniaturized devices, due to their robustness and high sensitivity of detection. Amongst the different optical investigation techniques, Raman spectroscopy has grown popular since it enables the non–invasive and label–free identification of chemical species, basing on the inelastically–scattered signal that emerges from a sample when irradiated by a coherent light source. Given their respective strengths, the union between microfluidics and Raman spectroscopy is potentially extremely useful. However, due to the weak nature of Raman scattering and the small sample volumes involved in microfluidics, an endeavour is needed to enhance the sensitivity of Raman–based LoC systems. To avoid the usage of bulky and expensive optical setups, an interesting option to perform on–chip Raman spectroscopy is to exploit optical fibres. This approach improves the portability, reduces costs and can help in limiting the noise of the measurement. This work presents an all–glass optofluidic LoC that enables in–fibre Raman spectroscopy of flowing samples. The adopted fabrication technique for the device is femtosecond–laser irradiation followed by chemical etching (FLICE). The operation of the device is characterised and a two–fold increase in its sensitivity is achieved by means of an integrated optical micromirror. The SNR improvement observed in this work hopes to push towards the realisation of more portable, low–cost, and real–time Raman applications
Graph Neural Networks based AutoEncoder in Reduced Order Modeling of Dynamical Systems
No full textLAUREA MAGISTRALENegli ultimi anni, la necessità di simulazioni efficienti e accurate di sistemi fisici complessi è diventata cruciale in vari ambiti scientifici e ingegneristici. Queste simulazioni, spesso ottenute dalla discretizzazione numerica di equazioni a derivate parziali (PDEs), sono fondamentali per comprendere e ottimizzare processi in campi come la fluidodinamica computazionale, la meccanica strutturale e l'elettromagnetismo. Tuttavia, l'elevato costo computazionale delle simulazioni numeriche tradizionali presenta significativi problemi per applicazioni che richiedono previsioni in tempo reale, quantificazione dell'incertezza e task di ottimizzazione.
Questo lavoro affronta tale limite sviluppando un nuovo framework di modellistica a ordine ridotto (ROM) che sfrutta le potenzialità delle reti neurali basate sui grafi (GNN). Questa scelta è motivata dal fatto che le tecniche ROM tradizionali, pur essendo efficaci in una vasta gamma di problemi, faticano ad affrontare geometrie complesse, non linearità e domini parametrizzati in cui la geometria stessa può variare. Le GNN, grazie alla loro capacità di elaborare dati strutturati a grafo e adattarsi a dimensioni e topologie di mesh diverse, offrono una soluzione promettente a queste problematiche.
Presentiamo un'architettura autoencoder basata sulle GNN, in grado di codificare in modo efficiente lo stato di un sistema dinamico in una rappresentazione latente compatta, per poi decodificarlo accuratamente nello spazio di stato originale. Questa architettura è particolarmente adatta a gestire la variabilità geometrica, essendo robusta rispetto a diverse configurazioni parametriche e domini eterogenei. Il framework proposto è validato tramite esperimenti numerici su diversi casi di studio, tra cui un problema di diffusione e trasporto (AD) e un flusso di Navier-Stokes intorno a un cilindro posizionato in punti distinti. I risultati dimostrano che il ROM basato su GNN riduce significativamente la complessità computazionale, mantenendo un'elevata accuratezza nella previsione delle dinamiche del sistema e che il modello proposto può essere generalizzato anche a configurazioni geometriche non viste in fase di addestramento.
In conclusione, questo lavoro dimostra l'efficacia delle GNN nell'estendere l'applicabilità dei ROM a una più ampia gamma di problemi complessi, non lineari e parametrizzati.In recent years, the need for efficient and accurate simulations of complex physical systems has become increasingly critical across various scientific and engineering disciplines. These simulations, often arising from the discretization of partial differential equations, are essential for understanding and optimizing processes in fields such as computational fluid dynamics, structural mechanics, and electromagnetism. However, the high computational cost of traditional numerical simulations poses significant challenges when considering applications that involve real-time predictions, uncertainty quantification, and optimization tasks.
This work addresses this limitation by developing a novel reduced order modeling (ROM) framework that leverages the capabilities of graph neural networks (GNNs). This choice is motivated by the fact that traditional ROM techniques, while effective for certain linear and affine problems, struggle with complex geometries, nonlinearity, and parameterized domains where the geometry itself can change. GNNs, with their ability to process graph structured data and adapt to varying mesh sizes and topologies, present a promising solution to overcome these limitations.
We introduce a GNN based autoencoder architecture that efficiently encodes the state of a dynamical system into a compact latent representation and accurately decodes it back to the original state space. This architecture is particularly well-suited for handling geometric variability, making it robust across different parametric configurations and diverse domains.
The proposed framework is validated through numerical experiments on different test cases, including an advection diffusion problem and a Navier-Stokes flow past a cylinder located in distinct positions. The results demonstrate that the GNN based ROM significantly reduces computational complexity while maintaining high accuracy in predicting system dynamics, generalizing also across unseen geometric configurations.
In conclusion, this work showcases the effectiveness of GNNs in extending the applicability of ROMs to a broader range of complex, nonlinear, and parameterized problems
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