Currently, there is a vast amount of research activity taking place into the development of new materials having unconventional properties and the respective technologies have been opening new eras through various applications for society. This new generation of materials, or metamaterials, have led to interesting physical properties previously thought impossible such as cloaking, negative refraction and materials that contract when heated. Most of those properties are realised in the dynamic response of the material. However, in these dynamic processes uncertainty remains as to whether these metamaterials undergo feasible deformations, remaining intact. Research into the latter is limited. Understanding this phenomenon is important in developing new metamaterials. Additionally it is crucial, for example, in larger structures such as multi-span bridges, pipelines and skyscrapers exposed to earthquakes and terrorist attacks, regularly faced in Europe and their effects can be catastrophic to human life. To accomplish this research, a significant multidisciplinary effort is required from applied mathematicians, engineers, computer scientists and industrialists closely collaborating towards this one goal. This timely project has two aims: (i) to create a well-rounded researcher capable of interacting with engineers and industrialists and (ii) this should be executed through the research into this area or more specifically the dynamic failure propagation in structured media under various loading conditions. This will be achieved through establishing an international and multidisciplinary long-standing collaboration between the European Fellow (EF), who is an applied mathematician, academic partner UniCA and industrial partner ES. Through this, a unique research environment will be created offering essential training not possible at the EF’s home institute, creating new skills that will complement the EF’s existing strengths to enable objectives (i) and (ii).

Mental disorders are associated with abnormal sensory information processing (SIP) at preadolescence, especially in males. Aberrant SIP is a neutral cross-disorder trait that can be translated between humans and animals and assessed as the inability to prevent/gate an overload of irrelevant information. The mechanisms underlying physiological and pathological SIP variability are unexplored. Particularly, the causative role of hyperdopaminergia, key to SIP deficits, has never been tested by isolating, spatially and temporally, this single neural component. How does this trait evolve into a mental disorder? Why does it occur more often in males? REDIRECT will capitalize on our rodent model of prenatal cannabis exposure (PCE), which is the first of its kind to offer, at preadolescence, a sex bias in susceptibility to SIP deficits upon acute exposure to stress or cannabis. This animal model is amenable to molecular interrogation to probe causality for those resilience-promoting factors preventing females from developing a hyperdopaminergia and SIP deficits. By combining viral strategies to trace and probe cell-type specific input-output reorganization of dopamine circuits (Aim 1), with single-cell transcriptome analyses (Aim 2), REDIRECT will decipher how female sex imposes distinct molecular changes to neurons and circuits, which are key to prevent the etiopathogenesis of SIP disorders. By testing selected candidate genes to probe causality for how sex modulates genes, developmental trajectories, and behaviour, we will decode (Aim 3) how discrete dopaminergic circuits can be reprogrammed sex-dependently. REDIRECT will causally disentangle how sex differently affects genes, circuits, and behaviour to inform novel sex-specific and age-tailored therapies for SIP deficits, a cross-disorder trait typical of common and severe mental illnesses, including autism, attention deficit hyperactivity disorder, obsessive-compulsive disorder and schizophrenia

The main objective of this project (DR VCoach) will be the following: “Design and implement a robotic coach able to propose a proper exercise schedule based on human directives, monitor the exercise performed by the patient/elder and correct it in case of mistakes”. The output of the project will be a robotic coach to assist the elders during their daily physical training. The robot will be able to understand verbal commands from the user (e.g. what will be the training schedule of today? Today I feel tired, can we do a lighter training?), to define the sequence of exercises to be performed, to show the exercises to the user (with a verbal description and performing them by it-self), to monitor the user performing the exercises using RGB cameras, to eventually find some errors in the execution and to suggest a correction to the mistake. The whole system can be divided into four modules: - Speech module: This is the module in charge of the vocal interaction between the robot and the elders. - Exercise scheduler: The role of this module is to break the selected exercise into atomic actions, and send these actions to the Error detector and Action recognition and prediction modules. - Error detector: The Error detector module analyses the results coming from the Action recognition and prediction module based on the required actions received by the Exercise scheduler. After evaluating the performed action, the module sends an evaluation report to the speech module in order to inform the elder. - Action recognition and prediction: This module has the dual task of recognising the action performed by the elder using the RGB videos coming from its embedded camera, and predicting the future viso-proprioceptive stimuli based on the action that is being performed. The system will be implemented on Zora (a NAO robot with a software layer to make it usable by non ICT people).