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Institution

Istituto Italiano di Tecnologia

FacilityGenoa, Italy
About: Istituto Italiano di Tecnologia is a facility organization based out in Genoa, Italy. It is known for research contribution in the topics: Humanoid robot & 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: Humanoid robot, Robot, Graphene, iCub, Population


Papers
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Journal ArticleDOI
TL;DR: A computational platform that integrates the analysis of copy number variations and somatic mutations and unravels the landscape of in-frame gene fusions in glioblastoma provides insights into the pathogenesis of gliOBlastoma and highlights new targets for therapeutic intervention.
Abstract: Glioblastoma is one of the most challenging forms of cancer to treat. Here we describe a computational platform that integrates the analysis of copy number variations and somatic mutations and unravels the landscape of in-frame gene fusions in glioblastoma. We found mutations with loss of heterozygosity in LZTR1, encoding an adaptor of CUL3-containing E3 ligase complexes. Mutations and deletions disrupt LZTR1 function, which restrains the self renewal and growth of glioma spheres that retain stem cell features. Loss-of-function mutations in CTNND2 target a neural-specific gene and are associated with the transformation of glioma cells along the very aggressive mesenchymal phenotype. We also report recurrent translocations that fuse the coding sequence of EGFR to several partners, with EGFR-SEPT14 being the most frequent functional gene fusion in human glioblastoma. EGFR-SEPT14 fusions activate STAT3 signaling and confer mitogen independence and sensitivity to EGFR inhibition. These results provide insights into the pathogenesis of glioblastoma and highlight new targets for therapeutic intervention.

454 citations

Journal ArticleDOI
TL;DR: The insertion of PbX2 into Cs4Pb X6 provides a means of accessing CsPbX3 nanocrystals in a wide variety of sizes, shapes, and compositions, an important aspect for the development of precisely tuned perovskite nanocrystal inks.
Abstract: We have developed a colloidal synthesis of nearly monodisperse nanocrystals of pure Cs4PbX6 (X = Cl, Br, I) and their mixed halide compositions with sizes ranging from 9 to 37 nm. The optical absorption spectra of these nanocrystals display a sharp, high energy peak due to transitions between states localized in individual PbX64– octahedra. These spectral features are insensitive to the size of the particles and in agreement with the features of the corresponding bulk materials. Samples with mixed halide composition exhibit absorption bands that are intermediate in spectral position between those of the pure halide compounds. Furthermore, the absorption bands of intermediate compositions broaden due to the different possible combinations of halide coordination around the Pb2+ ions. Both observations are supportive of the fact that the [PbX6]4– octahedra are electronically decoupled in these systems. Because of the large band gap of Cs4PbX6 (>3.2 eV), no excitonic emission in the visible range was observed...

453 citations

Journal ArticleDOI
TL;DR: The main purpose of this paper is to review the state-of-the-art on intermediate human–robot interfaces (bi-directional), robot control modalities, system stability, benchmarking and relevant use cases, and to extend views on the required future developments in the realm of human-robot collaboration.
Abstract: Recent technological advances in hardware design of the robotic platforms enabled the implementation of various control modalities for improved interactions with humans and unstructured environments. An important application area for the integration of robots with such advanced interaction capabilities is human---robot collaboration. This aspect represents high socio-economic impacts and maintains the sense of purpose of the involved people, as the robots do not completely replace the humans from the work process. The research community's recent surge of interest in this area has been devoted to the implementation of various methodologies to achieve intuitive and seamless human---robot-environment interactions by incorporating the collaborative partners' superior capabilities, e.g. human's cognitive and robot's physical power generation capacity. In fact, the main purpose of this paper is to review the state-of-the-art on intermediate human---robot interfaces (bi-directional), robot control modalities, system stability, benchmarking and relevant use cases, and to extend views on the required future developments in the realm of human---robot collaboration.

452 citations

Journal ArticleDOI
TL;DR: The discussion will use selected case studies to highlight how mechanistic investigations can be instrumental in guiding the invention and development of synthetically useful photocatalytic transformations.
Abstract: The fast-moving fields of photoredox and photocatalysis have recently provided fresh opportunities to expand the potential of synthetic organic chemistry. Advances in light-mediated processes have mainly been guided so far by empirical findings and the quest for reaction invention. The general perception, however, is that photocatalysis is entering a more mature phase where the combination of experimental and mechanistic studies will play a dominant role in sustaining further innovation. This Review outlines the key mechanistic studies to consider when developing a photochemical process, and the best techniques available for acquiring relevant information. The discussion will use selected case studies to highlight how mechanistic investigations can be instrumental in guiding the invention and development of synthetically useful photocatalytic transformations.

448 citations

Journal ArticleDOI
TL;DR: An approach based on HMM, GMR, and dynamical systems to allow robots to acquire new skills by imitation was presented and evaluated and applications on different kinds of robots were presented to highlight the flexibility of the proposed approach.
Abstract: We presented and evaluated an approach based on HMM, GMR, and dynamical systems to allow robots to acquire new skills by imitation. Using HMM allowed us to get rid of the explicit time dependency that was considered in our previous work [12], by encapsulating precedence information within the statistical representation. In the context of separated learning and reproduction processes, this novel formulation was systematically evaluated with respect to our previous approach, LWR [20], LWPR [21], and DMPs [13]. We finally presented applications on different kinds of robots to highlight the flexibility of the proposed approach in three different learning by imitation scenarios.

448 citations


Authors

Showing all 4601 results

NameH-indexPapersCitations
Marc G. Caron17367499802
Paolo Vineis134108886608
Michele Parrinello13363794674
Alex J. Barker132127384746
Tomaso Poggio13260888676
Shuai Liu129109580823
Giacomo Rizzolatti11729897242
Yehezkel Ben-Ari11045944293
Daniele Piomelli10450549009
Bruno Scrosati10358066572
Wolfgang J. Parak10246943307
Liberato Manna9849444780
Muhammad Imran94305351728
Ole Isacson9334530460
Luigi Ambrosio9376139688
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202313
2022109
20211,576
20201,618
20191,439
20181,381