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Institution

Polytechnic University of Turin

EducationTurin, Piemonte, Italy
About: Polytechnic University of Turin is a education organization based out in Turin, Piemonte, Italy. It is known for research contribution in the topics: Finite element method & Computer science. The organization has 11553 authors who have published 41395 publications receiving 789320 citations. The organization is also known as: POLITO & Politecnico di Torino.


Papers
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Journal ArticleDOI
TL;DR: This paper considers an alternative ‘randomized’ or ‘scenario’ approach for dealing with uncertainty in optimization, based on constraint sampling, and studies the constrained optimization problem resulting by taking into account only a finite set of N constraints, chosen at random among the possible constraint instances of the uncertain problem.
Abstract: Many engineering problems can be cast as optimization problems subject to convex constraints that are parameterized by an uncertainty or ‘instance’ parameter. Two main approaches are generally available to tackle constrained optimization problems in presence of uncertainty: robust optimization and chance-constrained optimization. Robust optimization is a deterministic paradigm where one seeks a solution which simultaneously satisfies all possible constraint instances. In chance-constrained optimization a probability distribution is instead assumed on the uncertain parameters, and the constraints are enforced up to a pre-specified level of probability. Unfortunately however, both approaches lead to computationally intractable problem formulations. In this paper, we consider an alternative ‘randomized’ or ‘scenario’ approach for dealing with uncertainty in optimization, based on constraint sampling. In particular, we study the constrained optimization problem resulting by taking into account only a finite set of N constraints, chosen at random among the possible constraint instances of the uncertain problem. We show that the resulting randomized solution fails to satisfy only a small portion of the original constraints, provided that a sufficient number of samples is drawn. Our key result is to provide an efficient and explicit bound on the measure (probability or volume) of the original constraints that are possibly violated by the randomized solution. This volume rapidly decreases to zero as N is increased.

734 citations

Journal ArticleDOI
TL;DR: It is shown that consensus clustering can be combined with any existing method in a self-consistent way, enhancing considerably both the stability and the accuracy of the resulting partitions.
Abstract: The community structure of complex networks reveals both their organization and hidden relationships among their constituents. Most community detection methods currently available are not deterministic, and their results typically depend on the specific random seeds, initial conditions and tie-break rules adopted for their execution. Consensus clustering is used in data analysis to generate stable results out of a set of partitions delivered by stochastic methods. Here we show that consensus clustering can be combined with any existing method in a self-consistent way, enhancing considerably both the stability and the accuracy of the resulting partitions. This framework is also particularly suitable to monitor the evolution of community structure in temporal networks. An application of consensus clustering to a large citation network of physics papers demonstrates its capability to keep track of the birth, death and diversification of topics.

727 citations

Journal ArticleDOI
TL;DR: A new mechanism leading to scale-free networks is proposed, which is called a good-get-richer mechanism, in which sites with larger fitness are more likely to become hubs (i.e., to be highly connected).
Abstract: A new mechanism leading to scale-free networks is proposed in this Letter. It is shown that, in many cases of interest, the connectivity power-law behavior is neither related to dynamical properties nor to preferential attachment. Assigning a quenched fitness value x(i) to every vertex, and drawing links among vertices with a probability depending on the fitnesses of the two involved sites, gives rise to what we call a good-get-richer mechanism, in which sites with larger fitness are more likely to become hubs (i.e., to be highly connected).

727 citations

Journal ArticleDOI
TL;DR: A three dimensional micromolding technique utilizing bioprinted agarose template fibers to fabricate microchannel networks with various architectural features within photocrosslinkable hydrogel constructs with useful applications in tissue engineering and organs on a chip is reported.
Abstract: Vascularization remains a critical challenge in tissue engineering. The development of vascular networks within densely populated and metabolically functional tissues facilitate transport of nutrients and removal of waste products, thus preserving cellular viability over a long period of time. Despite tremendous progress in fabricating complex tissue constructs in the past few years, approaches for controlled vascularization within hydrogel based engineered tissue constructs have remained limited. Here, we report a three dimensional (3D) micromolding technique utilizing bioprinted agarose template fibers to fabricate microchannel networks with various architectural features within photocrosslinkable hydrogel constructs. Using the proposed approach, we were able to successfully embed functional and perfusable microchannels inside methacrylated gelatin (GelMA), star poly(ethylene glycol-co-lactide) acrylate (SPELA), poly(ethylene glycol) dimethacrylate (PEGDMA) and poly(ethylene glycol) diacrylate (PEGDA) hydrogels at different concentrations. In particular, GelMA hydrogels were used as a model to demonstrate the functionality of the fabricated vascular networks in improving mass transport, cellular viability and differentiation within the cell-laden tissue constructs. In addition, successful formation of endothelial monolayers within the fabricated channels was confirmed. Overall, our proposed strategy represents an effective technique for vascularization of hydrogel constructs with useful applications in tissue engineering and organs on a chip.

726 citations

Journal ArticleDOI
TL;DR: This paper aims to offer a profound analysis of the interrelations between smart city components connecting the cornerstones of the triple helix, using the Analytic Network Process to model, cluster and begin measuring the performance of smart cities.
Abstract: This paper aims to offer a profound analysis of the interrelations between smart city components connecting the cornerstones of the triple helix. The triple helix model has emerged as a reference framework for the analysis of knowledge-based innovation systems, and relates the multiple and reciprocal relationships between the three main agencies in the process of knowledge creation and capitalization: university, industry and government. This analysis of the triple helix will be augmented using the Analytic Network Process to model, cluster and begin measuring the performance of smart cities. The model obtained allows interactions and feedbacks within and between clusters, providing a process to derive ratio scales priorities from elements. This offers a more truthful and realistic representation for supporting policy-making. The application of this model is still to be developed, but a full list of indicators, available at urban level, has been identified and selected from literature review.

723 citations


Authors

Showing all 11854 results

NameH-indexPapersCitations
Rodney S. Ruoff164666194902
Silvia Bordiga10749841413
Sergio Ferrara10572644507
Enrico Rossi10360641255
Stefano Passerini10277139119
James Barber10264242397
Markus J. Buehler9560933054
Dario Farina9483232786
Gabriel G. Katul9150634088
M. De Laurentis8427554727
Giuseppe Caire8282540344
Christophe Fraser7626429250
Erasmo Carrera7582923981
Andrea Califano7530531348
Massimo Inguscio7442721507
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023210
2022487
20212,789
20202,969
20192,779
20182,509