It enables a systemic and evolutionary development of people, organisations and territories by overcoming the criticality of traditional approaches, which get stuck because of rationalistic reductions in complexity, as well as lack of motivation. This responds to the social sustainability needs highlighted by the UN 2030 agenda. The methodology is based on 3 pillars:
Technologies
In this section it is possible to view, also through targeted research, the technologies inserted in the PROMO-TT Database. For further information on the technologies and to contact the CNR Research Teams who developed them, it is necessary to contact the Project Manager (see the references at the bottom of each record card).
Displaying results 16 - 30 of 32
Portable robotic device for bilateral neuromotor rehabilitation. An appropriate mechanical structure and a series of interchangeable accessories suitably designed allow the execution of various motor gestures of the upper limbs, involving different articulations and muscles. The possibility of being used with both limbs contributes to the recovery of motor coordination and facilitates the mechanism of brain plasticity. Some rotary axes the device is equipped with are motorized and sensorized.
The instrumentation is based on the electrical resistivity tomography (ERT) which is a non-invasive geophysical technology used to obtain information on anomalous bodies possibly present in the subsoil. The theoretical basis lies in the different electrical properties of the lithotypes present in the subsoil.
The NanoMicroFab infrastructure, support companies operating in the field of micro and nanoelectronics through the supply of materials, development of processes, design, fabrication and characterization of materials and devices. NanoMicroFab makes use of existing CNR facilities of the Institute of Microelectronics and Microsystems, the Institute of Photonics and Nanotechnologies and the Institute for the Structure of Matter and provides: • a complete line of development of devices based on wide band gap semiconductors.
Solid State Nuclear Magnetic Resonance spectroscopy (SSNMR) is today one of the most powerful techniques for characterizing solid and soft materials and systems. This spectroscopy allows the detailed characterization of structural and dynamic properties over large spatial (0.1-100 nm) and time (102-10-11 s) scales. Accessing these properties allows a deep knowledge of a material to be obtained and its design and optimization to be oriented.
The proposed technology deals with the development of active SERS (Surface Enhanced Raman Scattering) substrates ad hoc designed for diagnostics of cultural heritage. The substrates are prepared starting from common commercial 'polishing film' sheets (lapping optical fibers) showing an intrinsic roughness (48- 1000 nm) that favors the SERS effect. A pattern of silver or gold nanoparticles are deposited on these films through Pulsed Laser Deposition (PLD).
The instrument which is under development is a non-conventional portable Raman spectrometer. Raman spectrometers provide the molecular composition of the material surfaces, essential for their identification. The instrument peculiarity relies in the simultaneous acquisition of Raman spectra at imaged position and at different micrometric distances (offset) from the laser illumination area.
Recently, it has been demonstrated that Raman spectroscopy can play a fundamental role in assisting the work of the anatomopathologist by allowing classification of oncological samples with practically 100% accuracy in oncological diagnosis.
Network structures that require the use of a common database are affected by the risk of processing identification data that are necessary for sharing information and updating and processing data with equal access level between the network nodes. However, this sharing could lead risks of vulnerability when identification data are exchanged between the nodes of the network. The proposed information system involves the exchange of information by encrypting the identification data with an MD5 Hashing procedure (RFC1321).
SITODIET is an innovative software that supports a translational approach to health’s state. It integrates various sources of physiological, behavioral, and psychological data to reduce the risks associated with the onset of lifestyle-related diseases (primary prevention), to support health professionals in early diagnosis (secondary prevention) or to manage the personalized therapy’s patient (tertiary prevention). SITODIETcollects data automatically, through actigraphy tools, as wristband or smartwatch, or manually
The study of proteins is typically limited to notions, sometimes with the aid of virtual 3D models, obtained from visualization programs. A knowledge of this type, although useful, limits the ability to acquire a more direct knowledge, almost never leads to awareness of dimensions, and is particularly difficult for those who do not have a strong capacity for three-dimensional imagination.
The technology refers to a system for the safety and control of the mobility of vehicles, pedestrians, and mass transport users, in conventional and advanced contexts and is suitable for use as an infrastructure for the production/sharing of information and data, aimed at monitoring and intervention in critical areas by offering specific functions concerning the detection of potentially dangerous situations or the optimization of resources.
uManager is a management game designed to foster the development of young students' entrepreneurial skills and abilities. The game offers the opportunity to manage a tourist village, stimulating the skills of decision making and problem-solving in a simulated scenario adhering to the real one. uManager is suitable for use in the classroom or at a distance, in formal and informal contexts.
This form describes a programmable, autonomous and stand-alone imaging system for the acquisition and processing of images containing subjects whose size is larger than 1cm (e.g. gelatinous zooplankton, fishes, litter, manufacts), form the seafloor or along the water column, in shallow or deep waters. It is capable to recognize and classify the image content through pattern recognition algorithms that combine computer vision and artificial intelligence methodologies.