Modelling of Multi-Agent Systems: Experiences with Membrane Computing and Future Challenges

Formal modelling of Multi-Agent Systems (MAS) is a challenging task due to high complexity, interaction, parallelism and continuous change of roles and organisation between agents. In this paper we record our research experience on formal modelling of MAS. We review our research throughout the last decade, by describing the problems we have encountered and the decisions we have made towards resolving them and providing solutions. Much of this work involved membrane computing and classes of P Systems, such as Tissue and Population P Systems, targeted to the modelling of MAS whose dynamic structure is a prominent characteristic. More particularly, social insects (such as colonies of ants, bees, etc.), biology inspired swarms and systems with emergent behaviour are indicative examples for which we developed formal MAS models. Here, we aim to review our work and disseminate our findings to fellow researchers who might face similar challenges and, furthermore, to discuss important issues for advancing research on the application of membrane computing in MAS modelling.Comment: In Proceedings AMCA-POP 2010, arXiv:1008.314

A scoping review and thematic analysis of social and behavioural research among HIV-serodiscordant couples in high-income settings.

CAPRISA, 2015.Abstract available in pdf

Long-range allosteric signaling in red light-regulated diguanylyl cyclases.

Nature has evolved an astonishingly modular architecture of covalently linked protein domains with diverse functionalities to enable complex cellular networks that are critical for cell survival. The coupling of sensory modules with enzymatic effectors allows direct allosteric regulation of cellular signaling molecules in response to diverse stimuli. We present molecular details of red light-sensing bacteriophytochromes linked to cyclic dimeric guanosine monophosphate-producing diguanylyl cyclases. Elucidation of the first crystal structure of a full-length phytochrome with its enzymatic effector, in combination with the characterization of light-induced changes in conformational dynamics, reveals how allosteric light regulation is fine-tuned by the architecture and composition of the coiled-coil sensor-effector linker and also the central helical spine. We anticipate that consideration of molecular principles of sensor-effector coupling, going beyond the length of the characteristic linker, and the appreciation of dynamically driven allostery will open up new directions for the design of novel red light-regulated optogenetic tools

On the evolution of a multi-regional system

We study the effects of a decrease in trade costs on the spatial distribution of industry in a multi-regional economy, when a rise in the regional population of workers generates higher urban costs. We show that high and low trade costs imply that all regions involve a positive share of the industrial sector. When urban costs are linear, there exists a stable equilibrium for almost all values of trade costs. Furthermore, as trade costs fall, there is a path of stable equilibria such that the industry is, first, agglomerated into a decreasing number of regions and, then, dispersed among a growing number of regions. The second phase arises because of the increasing urban costs associated with the process of agglomeration

Experiences at ESOGÜ tourism camp: a grounded theory approach

Making tourism experiences more meaningful at the local level remains a challenge. Research using grounded theory (GT) was conducted in the context of Eskişehir Osmangazi Üniversitesi (ESOGÜ) Tourism Camp, and is significant in terms of boosting local tourism. This study aimed to generate a GT that could reveal the main concern emerging from the interactive processes at ESOGÜ Tourism Camp and explain how it was resolved. Classic GT allowed the researchers to examine a little-explored phenomenon from an internal perspective, without formulating a hypothesis or any pre-insights, by conceptualizing the participants’ authentic experiences. Following Glaser’s (2001) statement that “all is data,” the researchers chose ESOGÜ Tourism Camp, focusing on experiences during the process of producing photos. Based on the rules of classic GT, the researchers carried out the study as a cyclical process, whereby both data collection and analysis were implemented simultaneously (i.e., memos were written, the data was conceptualized and returned to collection again until theoretical saturation was achieved and a GT was formed). A new GT could promote local tourism and sustainable developmentBioekonomikos plėtros fakultetasVytauto Didžiojo universiteta

Monthly mean pressure reconstruction for the Late Maunder Minimum Period (AD 1675-1715)

The Late Maunder Minimum (LMM; 1675-1715) delineates a period with marked climate variability within the Little Ice Age in Europe. Gridded monthly mean surface pressure fields were reconstructed for this period for the eastern North Atlantic-European region (25°W-30°E and 35-70°N). These were based on continuous information drawn from proxy and instrumental data taken from several European data sites. The data include indexed temperature and rainfall values, sea ice conditions from northern Iceland and the Western Baltic. In addition, limited instrumental data, such as air temperature from central England (CET) and Paris, reduced mean sea level pressure (SLP) at Paris, and monthly mean wind direction in the Oresund (Denmark) are used. The reconstructions are based on a canonical correlation analysis (CCA), with the standardized station data as predictors and the SLP pressure fields as predictand. The CCA-based model was performed using data from the twentieth century. The period 1901-1960 was used to calibrate the statistical model, and the remaining 30 years (1961-1990) for the validation of the reconstructed monthly pressure fields. Assuming stationarity of the statistical relationships, the calibrated CCA model was then used to predict the monthly LMM SLP fields. The verification results illustrated that the regression equations developed for the majority of grid points contain good predictive skill. Nevertheless, there are seasonal and geographical limitations for which valid spatial SLP patterns can be reconstructed. Backward elimination techniques indicated that Paris station air pressure and temperature, CET, and the wind direction in the Oresund are the most important predictors, together sharing more than 65% of the total variance. The reconstructions are compared with additional data and subjectively reconstructed monthly pressure charts for the years 1675-1704. It is shown that there are differences between the two approaches. However, for extreme years the reconstructions are in good agreement