Dissecting the role of IGF2BP3 in the stress-adaptive response and in intercellular communication in Ewing Sarcoma.

Tumor microenvironment has emerged as key factor influencing tumor progression and metastatization. In this context, small vesicles produced by cancer cells can influence the fate of their surroundings via the horizontal transfer of specific molecular cargos. Ewing Sarcoma, the second most common bone tumor in young patients, presents early metastasis associated to worse prognosis. The RNA binding protein Insulin-like Growth Factor 2 mRNA Binding Protein 3 (IGF2BP3) exerts a pro-oncogenic role associated with metastasis formation and worse prognosis in Ewing Sarcoma. Our aim was to investigate the still unexplored role of IGF2BP3 in the stress-adaptive response to tumor microenvironment and in the interactions between Ewing Sarcoma cells. Hypoxia is a major feature of Ewing Sarcoma microenvironment and we demonstrated that IGF2BP3 can direct the CXCR4-mediated migratory response to CXCL12 in Ewing Sarcoma cells subjected to oxygen deprivation. We also discovered that the interaction between IGF2BP3 and CXCR4 is regulated through CD164 and which colocalize at plasma membrane level, upon CXCL12 exposure. Interestingly, high IGF2BP3 levels in Ewing Sarcoma metastatic lesions positively correlated with the expression of both CD164 and CXCR4, indicating the IGF2BP3/CD164/CXCR4 oncogenic axis as a critical modulator of Ewing Sarcoma metastatic progression. We demonstrated for the first time that IGF2BP3 is loaded into Ewing Sarcoma derived exosomes, accordingly to its cellular levels. We discovered that IGF2BP3+ exosomes carry high levels of IGF2BP3-client mRNAs involved in cellular migration, CD164 and IGF1R, and, by transferring this cargo, sustain the migratory abilities of receiving cells, induce a sharp up-regulation of CD164, CXCR4 and IGF1R and enhance the activation of AKT/mTOR and ERK down-stream signalling pathways. We demostrated that the pro-tumorigenic role of IGF2BP3 is not only exerted at cellular level, but that intercellular communication is crucial in the context of Ewing Sarcoma microenvironment.

Experimental analysis of the effect of the structure area on the PZT-based SHM systems

The structural health monitoring (SHM) systems based on electromechanical (E/M) impedance technique have been widely investigated. Although many studies indicate the reliability of this technique, some practical considerations still have to be considered in real applications. This paper presents an experimental analysis of the effect of the structure area on the system's performance. The results indicate that the sensitivity of the system to detect damage decreases significantly when the host structure has large cross-section area. Copyright © 2009 by ASME.

TORP: An open standard framework for humanoid robots

Humanoid robots are an extremely complex interdisciplinary research field. Particularly, the development of high size humanoid robots usually requires joint efforts and skills from groups that are in many different research centers around the world. However, there are serious constraints in this kind of collaborative development. Some efforts have been made in order to propose new software frameworks that can allow distributed development with also some degree of hardware abstraction, allowing software reuse in successive projects. However, computation represents only one of the dimensions in robotics tasks, and the need for reuse and exchange of full robot modules between groups are growing. Large advances could be reached if physical parts of a robot could be reused in a different robot constructed with other technologies by other researcher or group. This paper proposes a new robot framework, from now on called TORP (The Open Robot Project), that aims to provide a standard architecture in all dimensions (electrical, mechanical and computational) for this collaborative development. This methodology also represents an open project that is fully shared. In this paper, the first robot constructed following the TORP specification set is presented as well as the advances proposed for its improvement. © 2010 IEEE.

Justified assessments of service provider reputation

Abstract Reputation, influenced by ratings from past clients, is crucial for providers competing for custom. For new providers with less track record, a few negative ratings can harm their chances of growing. In the JASPR project, we aim to look at how to ensure automated reputation assessments are justified and informative. Even an honest balanced review of a service provision may still be an unreliable predictor of future performance if the circumstances differ. For example, a service may have previously relied on different sub-providers to now, or been affected by season-specific weather events. A common way to ameliorate the ratings that may not reflect future performance is by weighting by recency. We argue that better results are obtained by querying provenance records on how services are provided for the circumstances of provision, to determine the significance of past interactions. Informed by case studies in global logistics, taxi hire, and courtesy car leasing, we are going on to explore the generation of explanations for reputation assessments, which can be valuable both for clients and for providers wishing to improve their match to the market, and applying machine learning to predict aspects of service provision which may influence decisions on the appropriateness of a provider. In this talk, I will give an overview of the research conducted and planned on JASPR. Speaker Biography Dr Simon Miles Simon Miles is a Reader in Computer Science at King's College London, UK, and head of the Agents and Intelligent Systems group. He conducts research in the areas of normative systems, data provenance, and medical informatics at King's, and has published widely and manages a number of research projects in these areas. He was previously a researcher at the University of Southampton after graduating from his PhD at Warwick. He has twice been an organising committee member for the Autonomous Agents and Multi-Agent Systems conference series, and was a member of the W3C working group which published standards on interoperable provenance data in 2013.

Intelligent agents: are they feasible in swarm-array computing?

The work reported in this paper proposes 'Intelligent Agents', a Swarm-Array computing approach focused to apply autonomic computing concepts to parallel computing systems and build reliable systems for space applications. Swarm-array computing is a robotics a swarm robotics inspired novel computing approach considered as a path to achieve autonomy in parallel computing systems. In the intelligent agent approach, a task to be executed on parallel computing cores is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier agents and can be seamlessly transferred between cores in the event of a predicted failure, thereby achieving self-* objectives of autonomic computing. The approach is validated on a multi-agent simulator.

How the gut links innate and adaptive immunity.

Mucosal surfaces represent the main sites in which environmental microorganisms and antigens interact with the host. Sentinel cells, including epithelial cells, lumenal macrophages, and intraepithelial dendritic cells, continuously sense the environment and coordinate defenses for the protection of mucosal tissues. The mucosal epithelial cells are crucial actors in coordinating defenses. They sense the outside world and respond to environmental signals by releasing chemokines and cytokines that recruit inflammatory and immune cells to control potential infectious agents and to attract cells able to trigger immune responses. Among immune cells, dendritic cells (DC) play a key role in controlling adaptive immune responses, due to their capacity to internalize foreign materials and to present antigens to naive T and B lymphocytes, locally or in draining organized lymphoid tissues. Immune cells recruited in epithelial tissues can, in turn, act upon the epithelial cells and change their phenotype in a process referred to as epithelial metaplasia.

A model of Distributed Ayurvedic Diagnosis and Therapy System for Hridroga Using Agents

Diagnosis of Hridroga (cardiac disorders) in Ayurveda requires the combination of many different types of data, including personal details, patient symptoms, patient histories, general examination results, Ashtavidha pareeksha results etc. Computer-assisted decision support systems must be able to combine these data types into a seamless system. Intelligent agents, an approach that has been used chiefly in business applications, is used in medical diagnosis in this case. This paper is about a multi-agent system named “Distributed Ayurvedic Diagnosis and Therapy System for Hridroga using Agents” (DADTSHUA). It describes the architecture of the DADTSHUA model .This system is using mobile agents and ontology for passing data through the network. Due to this, transport delay can be minimized. It is a system which will be very helpful for the beginning physicians to eliminate his ambiguity in diagnosis and therapy. The system is implemented using Java Agent DEvelopment framework (JADE), which is a java-complaint mobile agent platform from TILab.

Applying autonomic computing concepts to parallel computing using intelligent agents

The work reported in this paper is motivated by the fact that there is a need to apply autonomic computing concepts to parallel computing systems. Advancing on prior work based on intelligent cores [36], a swarm-array computing approach, this paper focuses on ‘Intelligent agents’ another swarm-array computing approach in which the task to be executed on a parallel computing core is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier agents and is seamlessly transferred between cores in the event of a predicted failure, thereby achieving self-ware objectives of autonomic computing. The feasibility of the proposed swarm-array computing approach is validated on a multi-agent simulator.

Optimized Water Demand Management Through Intelligent Sensing And Analytics: The WISDOM Approach

New business and technology platforms are required to sustainably manage urban water resources [1,2]. However, any proposed solutions must be cognisant of security, privacy and other factors that may inhibit adoption and hence impact. The FP7 WISDOM project (funded by the European Commission - GA 619795) aims to achieve a step change in water and energy savings via the integration of innovative Information and Communication Technologies (ICT) frameworks to optimize water distribution networks and to enable change in consumer behavior through innovative demand management and adaptive pricing schemes [1,2,3]. The WISDOM concept centres on the integration of water distribution, sensor monitoring and communication systems coupled with semantic modelling (using ontologies, potentially connected to BIM, to serve as intelligent linkages throughout the entire framework) and control capabilities to provide for near real-time management of urban water resources. Fundamental to this framework are the needs and operational requirements of users and stakeholders at domestic, corporate and city levels and this requires the interoperability of a number of demand and operational models, fed with data from diverse sources such as sensor networks and crowsourced information. This has implications regarding the provenance and trustworthiness of such data and how it can be used in not only the understanding of system and user behaviours, but more importantly in the real-time control of such systems. Adaptive and intelligent analytics will be used to produce decision support systems that will drive the ability to increase the variability of both supply and consumption [3]. This in turn paves the way for adaptive pricing incentives and a greater understanding of the water-energy nexus. This integration is complex and uncertain yet being typical of a cyber-physical system, and its relevance transcends the water resource management domain. The WISDOM framework will be modeled and simulated with initial testing at an experimental facility in France (AQUASIM – a full-scale test-bed facility to study sustainable water management), then deployed and evaluated in in two pilots in Cardiff (UK) and La Spezia (Italy). These demonstrators will evaluate the integrated concept providing insight for wider adoption.

A multi-agent architecture for intelligent data analysis

The present study introduces a multi-agent architecture designed for doing automation process of data integration and intelligent data analysis. Different from other approaches the multi-agent architecture was designed using a multi-agent based methodology. Tropos, an agent based methodology was used for design. Based on the proposed architecture, we describe a Web based application where the agents are responsible to analyse petroleum well drilling data to identify possible abnormalities occurrence. The intelligent data analysis methods used was the Neural Network.

The Role of Parasitism in Adaptive Radiations - When Might Parasites Promote and When Might They Constrain Ecological Speciation?

Research on speciation and adaptive radiation has flourished during the past decades, yet factors underlying initiation of reproductive isolation often remain unknown. Parasites represent important selective agents and have received renewed attention in speciation research. We review the literature on parasite-mediated divergent selection in context of ecological speciation and present empirical evidence for three nonexclusive mechanisms by which parasites might facilitate speciation: reduced viability or fecundity of immigrants and hybrids, assortative mating as a pleiotropic by-product of host adaptation, and ecologically-based sexual selection. We emphasise the lack of research on speciation continuums, which is why no study has yet made a convincing case for parasite driven divergent evolution to initiate the emergence of reproductive isolation. We also point interest towards selection imposed by single vs. multiple parasite species, conceptually linking this to strength and multifariousness of selection. Moreover, we discuss how parasites, by manipulating behaviour or impairing sensory abilities of hosts, may change the form of selection that underlies speciation. We conclude that future studies should consider host populations at variable stages of the speciation process, and explore recurrent patterns of parasitism and resistance that could pinpoint the role of parasites in imposing the divergent selection that initiates ecological speciation.

Proceedings of the Eighth Australian and New Zealand Intelligent Information Systems Conference

These are the full proceedings of the conference.

Multi-Agent Information Processing and Adaptive Control in Global Telecommunication and Computer Networks

The problems and methods for adaptive control and multi-agent processing of information in global telecommunication and computer networks (TCN) are discussed. Criteria for controllability and communication ability (routing ability) of dataflows are described. Multi-agent model for exchange of divided information resources in global TCN has been suggested. Peculiarities for adaptive and intelligent control of dataflows in uncertain conditions and network collisions are analyzed.

Learning Data-Driven Models of Non-Verbal Behaviors for Building Rapport Using an Intelligent Virtual Agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness. Evidence-based patient-centered Brief Motivational Interviewing (BMI) interven- tions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary. Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems. To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].