Type IV Pilus-Mediated Inhibition of \u3ci\u3eAcinetobacter baumannii\u3c/i\u3e Biofilm Formation by Phenothiazine Compounds

Infections by pathogenic Acinetobacter species represent a significant burden on the health care system, despite their relative rarity, due to the difficulty of treating infections through oral antibiotics. Multidrug resistance is commonly observed in clinical Acinetobacter infections and multiple molecular mechanisms have been identified for this resistance, including multidrug efflux pumps, carbapenemase enzymes, and the formation of bacterial biofilm in persistent infections. Phenothiazine compounds have been identified as a potential inhibitor of type IV pilus production in multiple Gram-negative bacterial species. Here, we report the ability of two phenothiazines to inhibit type IV pilus-dependent surface (twitching) motility and biofilm formation in multiple Acinetobacter species. Biofilm formation was inhibited in both static and continuous flow models at micromolar concentrations without significant cytotoxicity, suggesting that type IV pilus biogenesis was the primary molecular target for these compounds. These results suggest that phenothiazines may be useful lead compounds for the development of biofilm dispersal agents against Gram-negative bacterial infections

A computational approach to implicit entities and events in text and discourse

In this paper we will focus on the notion of “implicit” or lexically unexpressed linguistic elements that are nonetheless necessary for a complete semantic interpretation of a text. We refer to “entities” and “events” because the recovery of the implicit material may affect all the modules of a system for semantic processing, from the grammatically guided components to the inferential and reasoning ones. Reference to the system GETARUNS offers one possible implementation of the algorithms and procedures needed to cope with the problem and enables us to deal with all the spectrum of phenomena. The paper will address at first the following three types of “implicit” entities and events: – the grammatical ones, as suggested by a linguistic theories like LFG or similar generative theories; – the semantic ones suggested in the FrameNet project, i.e. CNI, DNI, INI; – the pragmatic ones: here we will present a theory and an implementation for the recovery of implicit entities and events of (non-) standard implicatures. In particular we will show how the use of commonsense knowledge may fruitfully contribute to find relevant implied meanings. Last Implicit Entity only touched on, though for lack of space, is the Subject of Point of View, which is computed by Semantic Informational Structure and contributes the intended entity from whose point of view a given subjective statement is expressed

A game-based corpus for analysing the interplay between game context and player experience

Recognizing players’ affective state while playing video games has been the focus of many recent research studies. In this paper we describe the process that has been followed to build a corpus based on game events and recorded video sessions from human players while playing Super Mario Bros. We present different types of information that have been extracted from game context, player preferences and perception of the game, as well as user features, automatically extracted from video recordings. We run a number of initial experiments to analyse players’ behavior while playing video games as a case study of the possible use of the corpus.peer-reviewe

A Pilot Study with a Novel Setup for Collaborative Play of the Humanoid Robot KASPAR with children with autism

This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.This article describes a pilot study in which a novel experimental setup, involving an autonomous humanoid robot, KASPAR, participating in a collaborative, dyadic video game, was implemented and tested with children with autism, all of whom had impairments in playing socially and communicating with others. The children alternated between playing the collaborative video game with a neurotypical adult and playing the same game with the humanoid robot, being exposed to each condition twice. The equipment and experimental setup were designed to observe whether the children would engage in more collaborative behaviours while playing the video game and interacting with the adult than performing the same activities with the humanoid robot. The article describes the development of the experimental setup and its first evaluation in a small-scale exploratory pilot study. The purpose of the study was to gain experience with the operational limits of the robot as well as the dyadic video game, to determine what changes should be made to the systems, and to gain experience with analyzing the data from this study in order to conduct a more extensive evaluation in the future. Based on our observations of the childrens’ experiences in playing the cooperative game, we determined that while the children enjoyed both playing the game and interacting with the robot, the game should be made simpler to play as well as more explicitly collaborative in its mechanics. Also, the robot should be more explicit in its speech as well as more structured in its interactions. Results show that the children found the activity to be more entertaining, appeared more engaged in playing, and displayed better collaborative behaviours with their partners (For the purposes of this article, ‘partner’ refers to the human/robotic agent which interacts with the children with autism. We are not using the term’s other meanings that refer to specific relationships or emotional involvement between two individuals.) in the second sessions of playing with human adults than during their first sessions. One way of explaining these findings is that the children’s intermediary play session with the humanoid robot impacted their subsequent play session with the human adult. However, another longer and more thorough study would have to be conducted in order to better re-interpret these findings. Furthermore, although the children with autism were more interested in and entertained by the robotic partner, the children showed more examples of collaborative play and cooperation while playing with the human adult.Peer reviewe

Music-aided affective interaction between human and service robot

This study proposes a music-aided framework for affective interaction of service robots with humans. The framework consists of three systems, respectively, for perception, memory, and expression on the basis of the human brain mechanism. We propose a novel approach to identify human emotions in the perception system. The conventional approaches use speech and facial expressions as representative bimodal indicators for emotion recognition. But, our approach uses the mood of music as a supplementary indicator to more correctly determine emotions along with speech and facial expressions. For multimodal emotion recognition, we propose an effective decision criterion using records of bimodal recognition results relevant to the musical mood. The memory and expression systems also utilize musical data to provide natural and affective reactions to human emotions. For evaluation of our approach, we simulated the proposed human-robot interaction with a service robot, iRobiQ. Our perception system exhibited superior performance over the conventional approach, and most human participants noted favorable reactions toward the music-aided affective interaction.open0

Multimodal Detection of Engagement in Groups of Children Using Rank Learning

In collaborative play, children exhibit different levels of engagement. Some children are engaged with other children while some play alone. In this study, we investigated multimodal detection of individual levels of engagement using a ranking method and non-verbal features: turn-taking and body movement. Firstly, we automatically extracted turn-taking and body movement features in naturalistic and challenging settings. Secondly, we used an ordinal annotation scheme and employed a ranking method considering the great heterogeneity and temporal dynamics of engagement that exist in interactions. We showed that levels of engagement can be characterised by relative levels between children. In particular, a ranking method, Ranking SVM, outperformed a conventional method, SVM classification. While either turn-taking or body movement features alone did not achieve promising results, combining the two features yielded significant error reduction, showing their complementary power

Guidelines for Designing Social Robots as Second Language Tutors

In recent years, it has been suggested that social robots have potential as tutors and educators for both children and adults. While robots have been shown to be effective in teaching knowledge and skill-based topics, we wish to explore how social robots can be used to tutor a second language to young children. As language learning relies on situated, grounded and social learning, in which interaction and repeated practice are central, social robots hold promise as educational tools for supporting second language learning. This paper surveys the developmental psychology of second language learning and suggests an agenda to study how core concepts of second language learning can be taught by a social robot. It suggests guidelines for designing robot tutors based on observations of second language learning in human–human scenarios, various technical aspects and early studies regarding the effectiveness of social robots as second language tutors