681 research outputs found
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
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