Le nuove centralità del lavoro nel progetto urbano: appunti per una ricerca

Esempi internazionali ci mostrano intere città occupate a rivoluzionare i propri tessuti urbani innestandovi nuove strutture per la ricerca, l’innovazione e il trasferimento tecnologico a sostegno di settori economici più competitivi rispetto al nuovo quadro industriale globale. Le fabbriche, lungi dall’essere scomparse, hanno generalmente incrementato ovunque la propria produttività: le istanze di sostenibilità, la crescente quota di terziarizzazione e di complessità tecnologica dei processi produttivi ha tuttavia contribuito a modificare in parte il volto delle manifatture rispetto all’immagine ereditata dal secondo novecento. Forse sono maturi i tempi perché queste medie e grandi strutture per la ricerca e la produzione, così come le ormai sempre più diffuse tipologie per l’incubazione di start-up e per il co-working si svincolino dalla ristretta logica settoriale e dello zoning per essere invece considerati elementi fondanti della complessità e qualità dei luoghi urbani. Il ritorno e la valorizzazione dei luoghi della produzione in città, secondo ovviamente nuove configurazioni e prospettive rispetto al passato, potrebbe contribuire a incrementare il livello di urbanità dei quartieri della periferia storica, agendo ora come elementi di rigenerazione concentrata, ora come gangli diffusi

Panoptic Vision-Language Feature Fields

Recently, methods have been proposed for 3D open-vocabulary semantic segmentation. Such methods are able to segment scenes into arbitrary classes given at run-time using their text description. In this paper, we propose to our knowledge the first algorithm for open-vocabulary panoptic segmentation, simultaneously performing both semantic and instance segmentation. Our algorithm, Panoptic Vision-Language Feature Fields (PVLFF) learns a feature field of the scene, jointly learning vision-language features and hierarchical instance features through a contrastive loss function from 2D instance segment proposals on input frames. Our method achieves comparable performance against the state-of-the-art close-set 3D panoptic systems on the HyperSim, ScanNet and Replica dataset and outperforms current 3D open-vocabulary systems in terms of semantic segmentation. We additionally ablate our method to demonstrate the effectiveness of our model architecture. Our code will be available at https://github.com/ethz-asl/autolabel.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Continual Adaptation of Semantic Segmentation using Complementary 2D-3D Data Representations

Semantic segmentation networks are usually pre-trained once and not updated during deployment. As a consequence, misclassifications commonly occur if the distribution of the training data deviates from the one encountered during the robot's operation. We propose to mitigate this problem by adapting the neural network to the robot's environment during deployment, without any need for external supervision. Leveraging complementary data representations, we generate a supervision signal, by probabilistically accumulating consecutive 2D semantic predictions in a volumetric 3D map. We then train the network on renderings of the accumulated semantic map, effectively resolving ambiguities and enforcing multi-view consistency through the 3D representation. In contrast to scene adaptation methods, we aim to retain the previously-learned knowledge, and therefore employ a continual learning experience replay strategy to adapt the network. Through extensive experimental evaluation, we show successful adaptation to real-world indoor scenes both on the ScanNet dataset and on in-house data recorded with an RGB-D sensor. Our method increases the segmentation accuracy on average by 9.9% compared to the fixed pre-trained neural network, while retaining knowledge from the pre-training dataset.Comment: Accepted for IEEE Robotics and Automation Letters (R-AL 2022

CULTURAL IDENTITY AND CONSERVATION OF INDIGENOUS AND NATIVE DIVERSITY

The economic development of rural areas has rarely followed that of urban centres, with greater evidence of this in developing countries where the outlying communities have remained considerably more remote from the systems of cultural and economic growth. Even if this has had negative repercussions in terms of social equilibrium within the various countries, from a strictly agronomic point of view it has often resulted in the natural conservation of indigenous and native biodiversity. This has been affected by the natural and daily use of local plant extracts both for nutritional purposes and for a variety of other reasons. The exchange of genetic material between one community and another, often a sign of respect and friendship, has helped to increase plant diversity and to enhance its role in the everyday diet of rural populations. Any activity aimed at conserving biodiversity cannot disregard the fact that native plant species (and even more indigenous species) now play a vital role in the cultural identity of rural communities, and that making such communities aware of this precious asset can also play a strategic part in the idea of promoting biological diversity as a way of developing local economies. Such evidence clearly emerged through the various activities conducted in the context of the project, FAO GTF/RAF/426/ITA Promoting Origin-linked Quality Products in Four Countries in West Africa, financed by the Slow Food Foundation for Biodiversity Onlus. This project, conducted in 4 West African countries (Sierra Leone, Guinea Bissau, Senegal and Mali), aimed to carry out a study of these 4 states and draw up an inventory of the traditional plant and animal species, to examine the link between these and the diet of rural populations, and to assess the risks of genetic erosion by actions to safeguard the native biodiversity

Charge Recombination Kinetics of Bacterial Photosynthetic Reaction Centres Reconstituted in Liposomes: Deterministic Versus Stochastic Approach

In this theoretical work, we analyse the kinetics of charge recombination reaction after a light excitation of the Reaction Centres extracted from the photosynthetic bacterium Rhodobacter sphaeroides and reconstituted in small unilamellar phospholipid vesicles. Due to the compartmentalized nature of liposomes, vesicles may exhibit a random distribution of both ubiquinone molecules and the Reaction Centre protein complexes that can produce significant differences on the local concentrations from the average expected values. Moreover, since the amount of reacting species is very low in compartmentalized lipid systems the stochastic approach is more suitable to unveil deviations of the average time behaviour of vesicles from the deterministic time evolution

Unsupervised Continual Semantic Adaptation through Neural Rendering

An increasing amount of applications rely on data-driven models that are deployed for perception tasks across a sequence of scenes. Due to the mismatch between training and deployment data, adapting the model on the new scenes is often crucial to obtain good performance. In this work, we study continual multi-scene adaptation for the task of semantic segmentation, assuming that no ground-truth labels are available during deployment and that performance on the previous scenes should be maintained. We propose training a Semantic-NeRF network for each scene by fusing the predictions of a segmentation model and then using the view-consistent rendered semantic labels as pseudo-labels to adapt the model. Through joint training with the segmentation model, the Semantic-NeRF model effectively enables 2D-3D knowledge transfer. Furthermore, due to its compact size, it can be stored in a long-term memory and subsequently used to render data from arbitrary viewpoints to reduce forgetting. We evaluate our approach on ScanNet, where we outperform both a voxel-based baseline and a state-of-the-art unsupervised domain adaptation method.Comment: Zhizheng Liu and Francesco Milano share first authorship. Hermann Blum and Cesar Cadena share senior authorship. 18 pages, 7 figures, 10 table

Is it possible to assess the best mitral valve repair in the individual patient? Preliminary results of a finite element study from magnetic resonance imaging data

ObjectivesFinite element modeling was adopted to quantitatively compare, for the first time and on a patient-specific basis, the biomechanical effects of a broad spectrum of different neochordal implantation techniques for the repair of isolated posterior mitral leaflet prolapse.MethodsCardiac magnetic resonance images were acquired from 4 patients undergoing surgery. A patient-specific 3-dimensional model of the mitral apparatus and the motion of the annulus and papillary muscles were reconstructed. The location and extent of the prolapsing region were confirmed by intraoperative findings, and the mechanical properties of the mitral leaflets, chordae tendineae and expanded polytetrafluoroethylene neochordae were included. Mitral systolic biomechanics was simulated under preoperative conditions and after 5 different neochordal procedures: single neochorda, double neochorda, standard neochordal loop with 3 neochordae of the same length and 2 premeasured loops with 1 common neochordal loop and 3 different branched neochordae arising from it, alternatively one third and two thirds of the entire length.ResultsThe best repair in terms of biomechanics was achieved with a specific neochordal technique in the single patient, according to the location of the prolapsing region. However, all techniques achieved a slight reduction in papillary muscle forces and tension relief in intact native chordae proximal to the prolapsing region. Multiple neochordae implantation improved the repositioning of the prolapsing region below the annular plane and better redistributed mechanical stresses on the leaflet.ConclusionsAlthough applied on a small cohort of patients, systematic biomechanical differences were noticed between neochordal techniques, potentially affecting their short- to long-term clinical outcomes. This study opens the way to patient-specific optimization of neochordal techniques

Expression of ID4 protein in breast cancer cells induces reprogramming of tumour-associated macrophages

Background: As crucial regulators of the immune response against pathogens, macrophages have been extensively shown also to be important players in several diseases, including cancer. Specifically, breast cancer macrophages tightly control the angiogenic switch and progression to malignancy. ID4, a member of the ID (inhibitors of differentiation) family of proteins, is associated with a stem-like phenotype and poor prognosis in basal-like breast cancer. Moreover, ID4 favours angiogenesis by enhancing the expression of pro-angiogenic cytokines interleukin-8, CXCL1 and vascular endothelial growth factor. In the present study, we investigated whether ID4 protein exerts its pro-angiogenic function while also modulating the activity of tumour-associated macrophages in breast cancer. Methods: We performed IHC analysis of ID4 protein and macrophage marker CD68 in a triple-negative breast cancer series. Next, we used cell migration assays to evaluate the effect of ID4 expression modulation in breast cancer cells on the motility of co-cultured macrophages. The analysis of breast cancer gene expression data repositories allowed us to evaluate the ability of ID4 to predict survival in subsets of tumours showing high or low macrophage infiltration. By culturing macrophages in conditioned media obtained from breast cancer cells in which ID4 expression was modulated by overexpression or depletion, we identified changes in the expression of ID4-dependent angiogenesis-related transcripts and microRNAs (miRNAs, miRs) in macrophages by RT-qPCR. Results: We determined that ID4 and macrophage marker CD68 protein expression were significantly associated in a series of triple-negative breast tumours. Interestingly, ID4 messenger RNA (mRNA) levels robustly predicted survival, specifically in the subset of tumours showing high macrophage infiltration. In vitro and in vivo migration assays demonstrated that expression of ID4 in breast cancer cells stimulates macrophage motility. At the molecular level, ID4 protein expression in breast cancer cells controls, through paracrine signalling, the activation of an angiogenic programme in macrophages. This programme includes both the increase of angiogenesis-related mRNAs and the decrease of members of the anti-angiogenic miR-15b/107 group. Intriguingly, these miRNAs control the expression of the cytokine granulin, whose enhanced expression in macrophages confers increased angiogenic potential. Conclusions: These results uncover a key role for ID4 in dictating the behaviour of tumour-associated macrophages in breast cancer

Digitalizzazione nelle tecnologie per la salute: impatto sui livelli di governo del SSN

Il capitolo descrive il livello di digitalizzazione dei servizi sanitari analizzando in maniera critica il cambiamento avvenuto da pre a post pandemia da covid-19- Il capitolo riporta tutte le esperienze di digitalizzazione nelle regioni italiane con un focus specifico sull'aspetto della governance delle iniziative di digitalizzazione