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Institution

Polytechnic University of Milan

EducationMilan, Italy
About: Polytechnic University of Milan is a education organization based out in Milan, Italy. It is known for research contribution in the topics: Computer science & Finite element method. The organization has 18231 authors who have published 58416 publications receiving 1229711 citations. The organization is also known as: PoliMi & L-NESS.


Papers
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Journal ArticleDOI
TL;DR: It is shown that autistic-like symptoms are rescued on administration of AVP and OT to young Oxtr(-/-) adult animals and that intracerebral administration of both OT and AVP lowers aggression and fully reverts social and learning defects by acting on V1a receptors and that seizure susceptibility is antagonized by peripherally administered OT.

338 citations

Journal ArticleDOI
TL;DR: The scenario approach is illustrated at a tutorial level, focusing mainly on algorithmic aspects, and its versatility and virtues will be pointed out through a number of examples in model reduction, robust and optimal control.

337 citations

Journal ArticleDOI
TL;DR: This model develops the first spider silk mesoscale model, bridging the scales from Angstroms to tens to potentially hundreds of nanometers, and demonstrates that the specific nanoscale combination of a crystalline phase and a semiamorphous matrix is crucial to achieve the unique properties of silks.
Abstract: Spider dragline silk is one of the strongest, most extensible and toughest biological materials known, exceeding the properties of many engineered materials including steel. Silk features a hierarchical architecture where highly organized, densely H-bonded beta-sheet nanocrystals are arranged within a semiamorphous protein matrix consisting of 3(1)-helices and beta-turn protein structures. By using a bottom-up molecular-based approach, here we develop the first spider silk mesoscale model, bridging the scales from Angstroms to tens to potentially hundreds of nanometers. We demonstrate that the specific nanoscale combination of a crystalline phase and a semiamorphous matrix is crucial to achieve the unique properties of silks. Our results reveal that the superior mechanical properties of spider silk can be explained solely by structural effects, where the geometric confinement of beta-sheet nanocrystals, combined with highly extensible semiamorphous domains, is the key to reach great strength and great toughness, despite the dominance of mechanically inferior chemical interactions such as H-bonding. Our model directly shows that semiamorphous regions govern the silk behavior at small deformation, unraveling first when silk is being stretched and leading to the large extensibility of the material. Conversely, beta-sheet nanocrystals play a significant role in defining the mechanical behavior of silk at large-deformation. In particular, the ultimate tensile strength of silk is controlled by the strength of beta-sheet nanocrystals, which is directly related to their size, where small beta-sheet nanocrystals are crucial to reach outstanding levels of strength and toughness. Our results and mechanistic insight directly explain recent experimental results, where it was shown that a significant change in the strength and toughness of silk can be achieved solely by tuning the size of beta-sheet nanocrystals. Our findings help to unveil the material design strategy that enables silk to achieve superior material performance despite simple and inferior material constituents. This concept could lead to a new materials design paradigm, where enhanced functionality is not achieved using complex building blocks but rather through the utilization of simple repetitive constitutive elements arranged in hierarchical structures from nano to macro.

337 citations

Journal ArticleDOI
TL;DR: From QB to 0% Wmax there is a switch in respiratory muscle control, with immediate recruitment of rib cage and abdominal muscles, and a simple mechanism that increases drive equally to all three muscle groups allows the diaphragm to contract quasi-isotonically and act as a flow generator, while rib cage
Abstract: Aliverti, A., S. J. Cala, R. Duranti, G. Ferrigno, C. M. Kenyon, A. Pedotti, G. Scano, P. Sliwinski, Peter T. Macklem, and S. Yan. Human respiratory muscle actions and control during exercise.J. Ap...

337 citations

Journal ArticleDOI
TL;DR: The aim of this paper is to synthesize a controller via an event-triggered communication scheme such that not only the resulting closed-loop system is finite-time bounded and satisfies a prescribed performance level, but also the communication burden is reduced.
Abstract: This paper investigates the finite-time event-triggered $\mathcal{H}_{\infty }$ control problem for Takagi–Sugeno Markov jump fuzzy systems. Because of the sampling behaviors and the effect of network environment, the premise variables considered in this paper are subject to asynchronous constraints. The aim of this paper is to synthesize a controller via an event-triggered communication scheme such that not only the resulting closed-loop system is finite-time bounded and satisfies a prescribed $\mathcal{H}_{\infty }$ performance level, but also the communication burden is reduced. First, a sufficient condition is established for the finite-time bounded $\mathcal{H} _{\infty }$ performance analysis of the closed-loop fuzzy system with fully considering the asynchronous premises. Then, based on the derived condition, the method of the desired controller design is presented. Two illustrative examples are finally presented to demonstrate the practicability and efficacy of the proposed method.

337 citations


Authors

Showing all 18743 results

NameH-indexPapersCitations
Alex J. Barker132127384746
Pierluigi Zotto128119778259
Andrea C. Ferrari126636124533
Marco Dorigo10565791418
Marcello Giroletti10355841565
Luciano Gattinoni10361048055
Luca Benini101145347862
Alberto Sangiovanni-Vincentelli9993445201
Surendra P. Shah9971032832
X. Sunney Xie9822544104
Peter Nijkamp97240750826
Nicola Neri92112241986
Ursula Keller9293433229
A. Rizzi9165340038
Martin J. Blunt8948529225
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023302
2022813
20214,152
20204,301
20193,831
20183,767