Categories, Quantum Computing, and Swarm Robotics: A Case Study

The swarms of robots are examples of artificial collective intelligence, with simple individual autonomous behavior and emerging swarm effect to accomplish even complex tasks. Modeling approaches for robotic swarm development is one of the main challenges in this field of research. Here, we present a robot-instantiated theoretical framework and a quantitative worked-out example. Aiming to build up a general model, we first sketch a diagrammatic classification of swarms relating ideal swarms to existing implementations, inspired by category theory. Then, we propose a matrix representation to relate local and global behaviors in a swarm, with diagonal sub-matrices describing individual features and off-diagonal sub-matrices as pairwise interaction terms. Thus, we attempt to shape the structure of such an interaction term, using language and tools of quantum computing for a quantitative simulation of a toy model. We choose quantum computing because of its computational efficiency. This case study can shed light on potentialities of quantum computing in the realm of swarm robotics, leaving room for progressive enrichment and refinement

ANTERIOR OPEN BITE TREATED WITH E F APPLIANCE: A CASE REPORT

Aim. Current trends in pediatric orthodontics aim to identify incorrect development of occlusion and medium/lower facial third as early as possible. Functional appliances are a popular type of device used for treating malocclusion in patients who are growing. Among the functional orthodontic devices intended for this purpose, \u201cEducation Functional\u201d is highlighted. It was developed by Dr. Daniel Rollet. In fact, in the occlusal alterations, early preventive treatment with elastodontic devices resulted in avoiding dysfunctional forces from acting on the skeletal pattern, thus reaching a balance between bone basis and muscular components. This report describes a clinical case of a patient (9-year-old female) with anterior open bite associated to oral dysfunction, treated, in the mixed dentition, with EF-line appliance. Our purpose is to evaluate the effectiveness of this device for the correction of the dysmorphoses

Robots as intelligent assistants to face COVID-19 pandemic

Motivation: The epidemic at the beginning of this year, due to a new virus in the coronavirus family, is causing many deaths and is bringing the world economy to its knees. Moreover, situations of this kind are historically cyclical. The symptoms and treatment of infected patients are, for better or worse even for new viruses, always the same: More or less severe flu symptoms, isolation and full hygiene. By now man has learned how to manage epidemic situations, but deaths and negative effects continue to occur. What about technology? What effect has the actual technological progress we have achieved? In this review, we wonder about the role of robotics in the fight against COVID. It presents the analysis of scientific articles, industrial initiatives and project calls for applications from March to now highlighting how much robotics was ready to face this situation, what is expected from robots and what remains to do. Results: The analysis was made by focusing on what research groups offer as a means of support for therapies and prevention actions. We then reported some remarks on what we think is the state of maturity of robotics in dealing with situations like COVID-19

A global workspace theory model for trust estimation in human-robot interaction

Successful and genuine social connections between humans are based on trust, even more when the people involved have to collaborate to reach a shared goal. With the advent of new findings and technologies in the field of robotics, it appears that this same key factor that regulates relationships between humans also applies with the same importance to human-robot interactions (HRI). Previous studies have proven the usefulness of a robot able to estimate the trustworthiness of its human collaborators and in this position paper we discuss a method to extend an existing state-of-the-art trust model with considerations based on social cues such as emotions. The proposed model follows the Global Workspace Theory (GWT) principles to build a novel system able to combine multiple specialised expert systems to determine whether the partner can be considered trustworthy or not. Positive results would demonstrate the usefulness of using constructive biases to enhance the teaming skills of social robots

Inside the robot’s mind during human-robot interaction

Humans and robots collaborating and cooperating for pursuing a shared objective need to rely on the other for carrying out an effective decision process and for updating knowledge when necessary in a dynamic environment. Robots have to behave as they were human teammates. To model the cognitive process of robots during the interaction, we developed a cognitive architecture that we implemented employing the BDI (belief, desire, intention) agent paradigm. In this paper, we focus on how to let the robot show to the human its reasoning process and how its knowledge on the work environment grows. We realized a framework whose heart is a simulator that serves the human as a window on the robot’s mind

Robot’s Inner Speech Effects on Human Trust and Anthropomorphism

Inner Speech is an essential but also elusive human psychological process that refers to an everyday covert internal conversation with oneself. We argued that programming a robot with an overt self-talk system that simulates human inner speech could enhance both human trust and users’ perception of robot’s anthropomorphism, animacy, likeability, intelligence and safety. For this reason, we planned a pre-test/post-test control group design. Participants were divided in two different groups, one experimental group and one control group. Participants in the experimental group interacted with the robot Pepper equipped with an over inner speech system whereas participants in the control group interacted with the robot that produces only outer speech. Before and after the interaction, both groups of participants were requested to complete some questionnaires about inner speech and trust. Results showed differences between participants’ pretest and post-test assessment responses, suggesting that the robot’s inner speech influences in participants of experimental group the perceptions of animacy and intelligence in robot. Implications for these results are discussed

Recovering Sicilian Silk Heritage through Digital Technologies: The Case of Piraino's Collection

Textile conservation has given rise to small and medium-sized museums, usually with scarce resources. In Sicily, the little evidence that remains of silk production and opulent imports by the rich and powerful local aristocracy is kept in museums, parishes, and other cultural institutions. The documentation, dissemination, and enhancement of such a fragile heritage is today possible by means of technological tools that provide novel means to preserve, analyze, and exploit digital information. In this paper, we present some outcomes of the SILKNOW project, a project that applies computing research to the needs of diverse users (museums, educational institutions, the tourism industry, creative industries, media, etc.) and preserves the tangible and intangible heritage associated with silk. We show the methodology followed to build end users' needs into the Virtual Loom, a tool that deals with the 3D reconstruction of silk fabrics at the yarn level. We also provide a real example of how to integrate it at the museum level, specifically, at Piraino's Collection. The results demonstrate how small and medium-sized museums can access tools that will help them to carry out their daily tasks

Neurological Screening in Elderly Liver Transplantation Candidates: A Single Center Experience

Background: Cerebral small vessels disease (cSVD) is an age-related disorder and risk factor for stroke and cognitive/motor impairments. Neurological complications (NCs) are among the causes of adverse outcomes in older liver transplant recipients. This study sought to determine whether cSVD predicts acute NCs in over 65-year-old liver transplant patients. Methods: Data were collected, from a retrospective medical chart review, of 22 deceased donor liver transplant recipients aged 65 years or older with a pre-operative brain magnetic resonance imaging (MRI). We used the Fazekas score (0–3) as a quantitative measurement of the vascular lesion load seen in the MRI. We analyzed all post-operative acute NCs occurring during the hospital stay and any other non-NC. Results: cSVD was recognized in all patients. Neurological complications (NCs) occurred in 18.1% of patients with toxic-metabolic encephalopathy the most frequent diagnosis (13.64%). More severe cSVD was associated with seizures (p = 0.0362), longer hospital stay (p 0.0299), and disability (p 0.0134). In our elderly cohort, hepatic encephalopathy (HE) (p 0.0287) and ascites (p 0.0270) were predictors of NCs after liver transplantation. Ascites and/or variceal bleeding and severity of liver disease were associated with adverse post-operative outcomes. The small sample size limited the statistical analysis power. Conclusions: We present the preliminary data of a single-center retrospective study aimed at understanding the cSVD role on NCs and non-NCs after a liver transplantation in elderly patients. This would encourage a more appropriate multicenter prospective study that will definitely confirm if a neurological screening in old age liver transplant candidates is appropriate

Analysis of the gastrin-releasing peptide receptor gene in Italian patients with autism spectrum disorders

The gastrin-releasing peptide receptor (GRPR) was implicated for the first time in the pathogenesis of Autism spectrum disorders (ASD) by Ishikawa-Brush et al. [Ishikawa-Brush et al. (1997): Hum Mol Genet 6: 1241-1250]. Since this original observation, only one association study [Marui et al. (2004): Brain Dev 26: 5-7] has further investigated, though unsuccessfully, the involvement of the GRPR gene in ASD. With the aim of contributing further information to this topic we have sequenced the entire coding region and the intron/exon junctions of the GRPR gene in 149 Italian autistic patients. The results of this study led to the identification of four novel point mutations, two of which, that is, C6S and L181F, involve amino acid changes identified in two patients with ASD and Rett syndrome, respectively. Both the leucine at position 181 and the cysteine at position 6 are strongly conserved in vertebrates. C6S and L181F mutant proteins were expressed in COS-7 and BALB/3T3 cells, but they did not affect either GRP's binding affinity or its potency for stimulating phospholipase C-mediated production of inositol 1,4,5-trisphosphate. In summary, our results do not provide support for a major role of the GRPR gene in ASD in the population of patients we have studied. However, there is a potential role of C6S and L181F mutations on GRPR function, and possibly in the pathogenesis of the autistic disorders in the two patient

Decision Process in Human-Agent Interaction: Extending Jason Reasoning Cycle

The main characteristic of an agent is acting on behalf of humans. Then, agents are employed as modeling paradigms for complex systems and their implementation. Today we are witnessing a growing increase in systems complexity, mainly when the presence of human beings and their interactions with the system introduces a dynamic variable not easily manageable during design phases. Design and implementation of this type of systems highlight the problem of making the system able to decide in autonomy. In this work we propose an implementation, based on Jason, of a cognitive architecture whose modules allow structuring the decision-making process by the internal states of the agents, thus combining aspects of self-modeling and theory of the min