Istituto Italiano di Tecnologia

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.

Nanostructured carriers as innovative tools for cancer diagnosis and therapy.

Abstract: Cancer accounts for millions of deaths every year and, due to the increase and aging of the world population, the number of new diagnosed cases is continuously rising. Although many progresses in early diagnosis and innovative therapeutic protocols have been already set in clinical practice, still a lot of critical aspects need to be addressed in order to efficiently treat cancer and to reduce several drawbacks caused by conventional therapies. Nanomedicine has emerged as a very promising approach to support both early diagnosis and effective therapy of tumors, and a plethora of different inorganic and organic multifunctional nanomaterials have been ad hoc designed to meet the constant demand for new solutions in cancer treatment. Given their unique features and extreme versatility, nanocarriers represent an innovative and easily adaptable tool both for imaging and targeted therapy purposes, in order to improve the specific delivery of drugs administered to cancer patients. The current review reports an in-depth analysis of the most recent research studies aiming at developing both inorganic and organic materials for nanomedical applications in cancer diagnosis and therapy. A detailed overview of different approaches currently undergoing clinical trials or already approved in clinical practice is provided.

Learning collaborative impedance-based robot behaviors

Abstract: Research in learning from demonstration has focused on transferring movements from humans to robots. However, a need is arising for robots that do not just replicate the task on their own, but that also interact with humans in a safe and natural way to accomplish tasks cooperatively. Robots with variable impedance capabilities opens the door to new challenging applications, where the learning algorithms must be extended by encapsulating force and vision information. In this paper we propose a framework to transfer impedance-based behaviors to a torque-controlled robot by kinesthetic teaching. The proposed model encodes the examples as a task-parameterized statistical dynamical system, where the robot impedance is shaped by estimating virtual stiffness matrices from the set of demonstrations. A collaborative assembly task is used as testbed. The results show that the model can be used to modify the robot impedance along task execution to facilitate the collaboration, by triggering stiff and compliant behaviors in an on-line manner to adapt to the user's actions.

Influence of heat treatments on microstructure evolution and mechanical properties of Inconel 625 processed by laser powder bed fusion

Abstract: This study investigated the mechanical behaviour and microstructure of as-built and heat-treated Inconel 625 (IN625) samples processed by laser powder bed fusion (LPBF). This process offers freedom in design to build complex IN625 components in order to overcome extensive machining. However, post heat treatments must be performed to obtain specific mechanical properties to match industrial requirements. For this purpose, different heat treatments were performed on IN625 samples, and through hardness measurements, three different heat treatments were selected, as optimised conditions. A direct ageing, a solutioning and a solutioning followed by ageing treatments were chosen to study the effects of these specific heat treatments on the microstructure and tensile properties, comparing them to those of as-built condition. The tensile properties of as-built and selected heat-treated IN625 samples showed superior values to minimum requirements for wrought IN625 alloys, whereas the investigation on the microstructures and fracture surfaces of as-built and heat-treated IN625 contributed to an understanding of the tensile properties evolution. The high tensile strength of as-built samples essentially derived from very fine dendritic structures mainly below 1 µm with high dislocation density and nanometric MC carbides. The high tensile properties of ageing treatments performed at 700 °C for 24 h, whether directly aged or post-solutioning, were found to be primarily dependent on γ" phases (10–30 nm) and M23C6 carbides formation. By contrast, the tensile properties of solution-treated IN625 samples at 1150 °C for 2 h showed higher ductility coupled to lower strength than other conditions, due to the grain growth.

Monitoring spike train synchrony

Abstract: Recently, the SPIKE-distance has been proposed as a parameter-free and timescale-independent measure of spike train synchrony. This measure is time resolved since it relies on instantaneous estimates of spike train dissimilarity. However, its original definition led to spuriously high instantaneous values for eventlike firing patterns. Here we present a substantial improvement of this measure that eliminates this shortcoming. The reliability gained allows us to track changes in instantaneous clustering, i.e., time-localized patterns of (dis)similarity among multiple spike trains. Additional new features include selective and triggered temporal averaging as well as the instantaneous comparison of spike train groups. In a second step, a causal SPIKE-distance is defined such that the instantaneous values of dissimilarity rely on past information only so that time-resolved spike train synchrony can be estimated in real time. We demonstrate that these methods are capable of extracting valuable information from field data by monitoring the synchrony between neuronal spike trains during an epileptic seizure. Finally, the applicability of both the regular and the real-time SPIKE-distance to continuous data is illustrated on model electroencephalographic (EEG) recordings.