Institution
Istituto Italiano di Tecnologia
Facility•Genoa, Italy•
About: Istituto Italiano di Tecnologia is a facility organization based out in Genoa, Italy. It is known for research contribution in the topics: Robot & Humanoid robot. The organization has 4561 authors who have published 14595 publications receiving 437558 citations. The organization is also known as: Italian Institute of Technology & IIT.
Topics: Robot, Humanoid robot, Graphene, iCub, Nanoparticle
Papers published on a yearly basis
Papers
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TL;DR: A neural network potential trained on a multithermal–multibaric DFT data for the study of the phase diagram of gallium in a wide temperature and pressure range is demonstrated.
Abstract: Elemental gallium possesses several intriguing properties, such as a low melting point, a density anomaly and an electronic structure in which covalent and metallic features coexist. In order to simulate this complex system, we construct an ab initio quality interaction potential by training a neural network on a set of density functional theory calculations performed on configurations generated in multithermal–multibaric simulations. Here we show that the relative equilibrium between liquid gallium, α-Ga, β-Ga, and Ga-II is well described. The resulting phase diagram is in agreement with the experimental findings. The local structure of liquid gallium and its nucleation into α-Ga and β-Ga are studied. We find that the formation of metastable β-Ga is kinetically favored over the thermodinamically stable α-Ga. Finally, we provide insight into the experimental observations of extreme undercooling of liquid Ga. Exploring nucleation processes of gallium by molecular simulation is extremely challenging due to its structural complexity. Here the authors demonstrate a neural network potential trained on a multithermal–multibaric DFT data for the study of the phase diagram of gallium in a wide temperature and pressure range.
107 citations
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107 citations
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TL;DR: Experimental results performed on the Center for Advanced Studies in Adaptive Systems datasets show that the proposed LSTM-based approaches outperform existing DL and ML methods, giving superior results compared to the existing literature.
107 citations
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TL;DR: This review highlights recent advances in the development of heavy-metal-free nanocrystals within the context of specific photonic applications and describes strategies to transfer some of the advantageous nanocrystal features such as shape control to non-toxic materials.
Abstract: Colloidal nanocrystals – produced in a growing variety of shapes, sizes and compositions – are rapidly developing into a new generation of photonic materials, spanning light emitting as well as energy harvesting applications. Precise tailoring of their optoelectronic properties enables them to satisfy disparate application specific requirements. However, the presence of toxic heavy metals such as cadmium and lead in some of the most mature nanocrystals is a serious drawback which may ultimately preclude their use in consumer applications. Although the pursuit of non-toxic alternatives has occurred in parallel to the well-developed Cd- and Pb-based nanocrystals, synthetic challenges have, until recently, curbed progress. In this review, we highlight recent advances in the development of heavy-metal-free nanocrystals within the context of specific photonic applications. We also describe strategies to transfer some of the advantageous nanocrystal features such as shape control to non-toxic materials. Finally, we present recent developments that have the potential to make substantial impacts on the quest to attain a balance between performance and sustainability in photonics.
107 citations
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TL;DR: This work lays the groundwork for exploiting oncogenic mechanosignalling as a vulnerability at the onset of tumorigenesis, including tumour prevention strategies.
Abstract: Defining the interplay between the genetic events and microenvironmental contexts necessary to initiate tumorigenesis in normal cells is a central endeavour in cancer biology. We found that receptor tyrosine kinase (RTK)–Ras oncogenes reprogram normal, freshly explanted primary mouse and human cells into tumour precursors, in a process requiring increased force transmission between oncogene-expressing cells and their surrounding extracellular matrix. Microenvironments approximating the normal softness of healthy tissues, or blunting cellular mechanotransduction, prevent oncogene-mediated cell reprogramming and tumour emergence. However, RTK–Ras oncogenes empower a disproportional cellular response to the mechanical properties of the cell’s environment, such that when cells experience even subtle supra-physiological extracellular-matrix rigidity they are converted into tumour-initiating cells. These regulations rely on YAP/TAZ mechanotransduction, and YAP/TAZ target genes account for a large fraction of the transcriptional responses downstream of oncogenic signalling. This work lays the groundwork for exploiting oncogenic mechanosignalling as a vulnerability at the onset of tumorigenesis, including tumour prevention strategies. Receptor tyrosine kinase (RTK)–Ras oncogenes have now been shown to reprogram normal primary human and mouse cells into tumour precursors by empowering cellular mechanotransduction, in a process requiring permissive extracellular-matrix rigidity and intracellular YAP/TAZ/Rac mechanical signalling sustained by activated oncogenes.
107 citations
Authors
Showing all 4601 results
Name | H-index | Papers | Citations |
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Marc G. Caron | 173 | 674 | 99802 |
Paolo Vineis | 134 | 1088 | 86608 |
Michele Parrinello | 133 | 637 | 94674 |
Alex J. Barker | 132 | 1273 | 84746 |
Tomaso Poggio | 132 | 608 | 88676 |
Shuai Liu | 129 | 1095 | 80823 |
Giacomo Rizzolatti | 117 | 298 | 97242 |
Yehezkel Ben-Ari | 110 | 459 | 44293 |
Daniele Piomelli | 104 | 505 | 49009 |
Bruno Scrosati | 103 | 580 | 66572 |
Wolfgang J. Parak | 102 | 469 | 43307 |
Liberato Manna | 98 | 494 | 44780 |
Muhammad Imran | 94 | 3053 | 51728 |
Ole Isacson | 93 | 345 | 30460 |
Luigi Ambrosio | 93 | 761 | 39688 |