A multi-agent system for pervasive healthcare

Wireless technology based pervasive healthcare has been proposed in many applications such as disease management and accident prevention for cost saving and promoting citizen’s wellbeing. However, the emphasis so far is on the artefacts with limited attentions to guiding the development of an effective and efficient solution for pervasive healthcare. Therefore, this paper aims to propose a framework of multi-agent systems design for pervasive healthcare by adopting the concept of pervasive informatics and using the methods of organisational semiotics. The proposed multi-agent system for pervasive healthcare utilises sensory information to support healthcare professionals for providing appropriate care. The key contributions contain theoretical aspect and practical aspect. In theory, this paper articulates the information interactions between the pervasive healthcare environment and stakeholders by using the methods of organisational semiotics; in practice, the proposed framework improves the healthcare quality by providing appropriate medical attentions when and as needed. In this paper, both systems and functional architecture of the multi-agent system are elaborated with the use of wireless technologies such as RFID and wireless sensor networks. The future study will focus on the implementation of the proposed framework.

A semiotic approach of multi-agent simulation for policy evaluation

Nowadays the changing environment becomes the main challenge for most of organizations, since they have to evaluate proper policies to adapt to the environment. In this paper, we propose a multi-agent simulation method to evaluate policies based on complex adaptive system theory. Furthermore, we propose a semiotic EDA (Epistemic, Deontic, Axiological) agent model to simulate agent's behavior in the system by incorporating the social norms reflecting the policy. A case study is also provided to validate our approach. Our research present better adaptability and validity than the qualitative analysis and experiment approach and the semiotic agent model provides high creditability to simulate agents' behavior.

Cost function for sub-agent elements in multi-agent energy management system

Distributed generation plays a key role in reducing CO2 emissions and losses in transmission of power. However, due to the nature of renewable resources, distributed generation requires suitable control strategies to assure reliability and optimality for the grid. Multi-agent systems are perfect candidates for providing distributed control of distributed generation stations as well as providing reliability and flexibility for the grid integration. The proposed multi-agent energy management system consists of single-type agents who control one or more gird entities, which are represented as generic sub-agent elements. The agent applies one control algorithm across all elements and uses a cost function to evaluate the suitability of the element as a supplier. The behavior set by the agent's user defines which parameters of an element have greater weight in the cost function, which allows the user to specify the preference on suppliers dynamically. This study shows the ability of the multi-agent energy management system to select suppliers according to the selection behavior given by the user. The optimality of the supplier for the required demand is ensured by the cost function based on the parameters of the element.

Efficient animal-serum free 3D cultivation method for adult human neural crest-derived stem cell therapeutics

Due to their broad differentiation potential and their persistence into adulthood, human neural crest-derived stem cells (NCSCs) harbour great potential for autologous cellular therapies, which include the treatment of neurodegenerative diseases and replacement of complex tissues containing various cell types, as in the case of musculoskeletal injuries. The use of serum-free approaches often results in insufficient proliferation of stem cells and foetal calf serum implicates the use of xenogenic medium components. Thus, there is much need for alternative cultivation strategies. In this study we describe for the first time a novel, human blood plasma based semi-solid medium for cultivation of human NCSCs. We cultivated human neural crest-derived inferior turbinate stem cells (ITSCs) within a blood plasma matrix, where they revealed higher proliferation rates compared to a standard serum-free approach. Three-dimensionality of the matrix was investigated using helium ion microscopy. ITSCs grew within the matrix as revealed by laser scanning microscopy. Genetic stability and maintenance of stemness characteristics were assured in 3D cultivated ITSCs, as demonstrated by unchanged expression profile and the capability for self-renewal. ITSCs pre-cultivated in the 3D matrix differentiated efficiently into ectodermal and mesodermal cell types, particularly including osteogenic cell types. Furthermore, ITSCs cultivated as described here could be easily infected with lentiviruses directly in substrate for potential tracing or gene therapeutic approaches. Taken together, the use of human blood plasma as an additive for a completely defined medium points towards a personalisable and autologous cultivation of human neural crest-derived stem cells under clinical grade conditions.

Improved method for ex ovo-cultivation of developing chicken embryos for human stem cell xenografts

The characterization of human stem cells for the usability in regenerative medicine is particularly based on investigations regarding their differentiation potential in vivo. In this regard, the chicken embryo model represents an ideal model organism. However, the access to the chicken embryo is only achievable by windowing the eggshell resulting in limited visibility and accessibility in subsequent experiments. On the contrary, ex ovo-culture systems avoid such negative side effects. Here, we present an improved ex ovo-cultivation method enabling the embryos to survive 13 days in vitro. Optimized cultivation of chicken embryos resulted in a normal development regarding their size and weight. Our ex ovo-approach closely resembles the development of chicken embryos in ovo, as demonstrated by properly developed nervous system, bones, and cartilage at expected time points. Finally, we investigated the usability of our method for trans-species transplantation of adult stem cells by injecting human neural crest-derived stem cells into late Hamburger and Hamilton stages (HH26-HH28/E5-E6) of ex ovo-incubated embryos. We demonstrated the integration of human cells allowing experimentally easy investigation of the differentiation potential in the proper developmental context. Taken together, this ex ovo-method supports the prolonged cultivation of properly developing chicken embryos enabling integration studies of xenografted mammalian stem cells at late developmental stages.

Regulation of early steps of GPVI signal transduction by phosphatases: a systems biology approach

We present a data-driven mathematical model of a key initiating step in platelet activation, a central process in the prevention of bleeding following Injury. In vascular disease, this process is activated inappropriately and causes thrombosis, heart attacks and stroke. The collagen receptor GPVI is the primary trigger for platelet activation at sites of injury. Understanding the complex molecular mechanisms initiated by this receptor is important for development of more effective antithrombotic medicines. In this work we developed a series of nonlinear ordinary differential equation models that are direct representations of biological hypotheses surrounding the initial steps in GPVI-stimulated signal transduction. At each stage model simulations were compared to our own quantitative, high-temporal experimental data that guides further experimental design, data collection and model refinement. Much is known about the linear forward reactions within platelet signalling pathways but knowledge of the roles of putative reverse reactions are poorly understood. An initial model, that includes a simple constitutively active phosphatase, was unable to explain experimental data. Model revisions, incorporating a complex pathway of interactions (and specifically the phosphatase TULA-2), provided a good description of the experimental data both based on observations of phosphorylation in samples from one donor and in those of a wider population. Our model was used to investigate the levels of proteins involved in regulating the pathway and the effect of low GPVI levels that have been associated with disease. Results indicate a clear separation in healthy and GPVI deficient states in respect of the signalling cascade dynamics associated with Syk tyrosine phosphorylation and activation. Our approach reveals the central importance of this negative feedback pathway that results in the temporal regulation of a specific class of protein tyrosine phosphatases in controlling the rate, and therefore extent, of GPVI-stimulated platelet activation.

GALAXY EVOLUTION IN A COMPLEX ENVIRONMENT: A MULTI-WAVELENGTH STUDY OF HCG 7

The environment where galaxies are found heavily influences their evolution. Close groupings, like the ones in the cores of galaxy clusters or compact groups, evolve in ways far more dramatic than their isolated counterparts. We have conducted a multi-wavelength study of Hickson Compact Group 7 (HCG 7), consisting of four giant galaxies: three spirals and one lenticular. We use Hubble Space Telescope (HST) imaging to identify and characterize the young and old star cluster populations. We find young massive clusters (YMCs) mostly in the three spirals, while the lenticular features a large, unimodal population of globular clusters (GCs) but no detectable clusters with ages less than a few Gyr. The spatial and approximate age distributions of the similar to 300 YMCs and similar to 150 GCs thus hint at a regular star formation history in the group over a Hubble time. While at first glance the HST data show the galaxies as undisturbed, our deep ground-based, wide-field imaging that extends the HST coverage reveals faint signatures of stellar material in the intragroup medium (IGM). We do not, however, detect the IGM in H I or Chandra X-ray observations, signatures that would be expected to arise from major mergers. Despite this fact, we find that the H I gas content of the individual galaxies and the group as a whole are a third of the expected abundance. The appearance of quiescence is challenged by spectroscopy that reveals an intense ionization continuum in one galaxy nucleus, and post-burst characteristics in another. Our spectroscopic survey of dwarf galaxy members yields a single dwarf elliptical galaxy in an apparent stellar tidal feature. Based on all this information, we suggest an evolutionary scenario for HCG 7, whereby the galaxies convert most of their available gas into stars without the influence of major mergers and ultimately result in a dry merger. As the conditions governing compact groups are reminiscent of galaxies at intermediate redshift, we propose that HCGs are appropriate for studying galaxy evolution at z similar to 1-2.

Long-Term Culture of Mouse Embryonic Stem Cell-Derived Adherent Neurospheres and Functional Neurons

Innumerous protocols, using the mouse embryonic stem (ES) cells as model for in vitro study of neurons functional properties and features, have been developed. Most of these protocols are short lasting, which, therefore, does not allow a careful analysis of the neurons maturation, aging, and death processes. We describe here a novel and efficient long-lasting protocol for in vitro ES cells differentiation into neuronal cells. It consists of obtaining embryoid bodies, followed by induction of neuronal differentiation with retinoic acid of nonadherent embryoid bodies (three-dimensional model), which further allows their adherence and formation of adherent neurospheres (AN, bi-dimensional model). The AN can be maintained for at least 12 weeks in culture under repetitive mechanical splitting, providing a constant microenvironment (in vitro niche) for the neuronal progenitor cells avoiding mechanical dissociation of AN. The expression of neuron-specific proteins, such as nestin, sox1, beta III-tubulin, microtubule-associated protein 2, neurofilament medium protein, Tau, neuronal nuclei marker, gamma-aminobutyric acid, and 5-hydroxytryptamine, were confirmed in these cells maintained during 3 months under several splitting. Additionally, expression pattern of microtubule-associated proteins, such as lissencephaly (Lis1) and nuclear distribution element-like (Ndel1), which were shown to be essential for differentiation and migration of neurons during embryogenesis, was also studied. As expected, both proteins were expressed in undifferentiated ES cells, AN, and nonrosette neurons, although presenting different spatial distribution in AN. In contrast to previous studies, using cultured neuronal cells derived from embryonic and adult tissues, only Ndel1 expression was observed in the centrosome region of early neuroblasts from AN. Mature neurons, obtained from ES cells in this work, display ionic channels and oscillations of membrane electrical potential typical of electrically excitable cells, which is a characteristic feature of the functional central nervous system (CNS) neurons. Taken together, our study demonstrated that AN are a long-term culture of neuronal cells that can be used to analyze the process of neuronal differentiation dynamics. Thus, the protocol described here provides a new experimental model for studying neurological diseases associated with neuronal differentiation during early development, as well as it represents a novel source of functional cells that can be used as tools for testing the effects of toxins and/or drugs on neuronal cells.

Involvement of Eukaryotic Translation Initiation Factor 5A (eIF5A) in Skeletal Muscle Stem Cell Differentiation

The eukaryotic translation initiation factor 5A (eIF5A) contains a special amino acid residue named hypusine that is required for its activity, being produced by a post-translational modification using spermidine as substrate. Stem cells from rat skeletal muscles (satellite cells) were submitted to differentiation and an increase of eIF5A gene expression was observed. Higher content of eIF5A protein was found in satellite cells on differentiation in comparison to non-differentiated satellite cells and skeletal muscle. The treatment with NI-guanyl- 1,7-diaminoheptane (GC7), a hypusination inhibitor, reversibly abolished the differentiation process. In association with the differentiation blockage, an increase of glucose consumption and lactate production and a decrease of glucose and palmitic acid oxidation were observed. A reduction in cell proliferation and protein synthesis was also observed. L-Arginine, a spermidine precursor and partial suppressor of muscle dystrophic phenotype, partially abolished the GC7 inhibitory effect on satellite cell differentiation. These results reveal a new physiological role for eIF5A and contribute to elucidate the molecular mechanisms involved in muscle regeneration.

Designing Agent-Oriented Systems by Analysing Agent Interactions

We propose a preliminary methodology for agent-oriented software engineering based on the idea of agent interaction analysis. This approach uses interactions between undetermined agents as the primary component of analysis and design. Agents as a basis for software engineering are useful because they provide a powerful and intuitive abstraction which can increase the comprehensiblity of a complex design. The paper describes a process by which the designer can derive the interactions that can occur in a system satisfying the given requirements and use them to design the structure of an agent-based system, including the identification of the agents themselves. We suggest that this approach has the flexibility necessary to provide agent-oriented designs for open and complex applications, and has value for future maintenance and extension of these systems.

Experience generalization for multi-agent reinforcement learning

On-line learning methods have been applied successfully in multi-agent systems to achieve coordination among agents. Learning in multi-agent systems implies in a non-stationary scenario perceived by the agents, since the behavior of other agents may change as they simultaneously learn how to improve their actions. Non-stationary scenarios can be modeled as Markov Games, which can be solved using the Minimax-Q algorithm a combination of Q-learning (a Reinforcement Learning (RL) algorithm which directly learns an optimal control policy) and the Minimax algorithm. However, finding optimal control policies using any RL algorithm (Q-learning and Minimax-Q included) can be very time consuming. Trying to improve the learning time of Q-learning, we considered the QS-algorithm. in which a single experience can update more than a single action value by using a spreading function. In this paper, we contribute a Minimax-QS algorithm which combines the Minimax-Q algorithm and the QS-algorithm. We conduct a series of empirical evaluation of the algorithm in a simplified simulator of the soccer domain. We show that even using a very simple domain-dependent spreading function, the performance of the learning algorithm can be improved.

Multi-Agent Simulation of Urban Social Dynamics for Spatial Load Forecasting

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