Solution concepts in two-person multicriteria games

In this paper, we propose new solution concepts for multicriteria games and compare them with existing ones. The general setting is that of two-person finite games in normal form (matrix games) with pure and mixed strategy sets for the players. The notions of efficiency (Pareto optimality), security levels, and response strategies have all been used in defining solutions ranging from equilibrium points to Pareto saddle points. Methods for obtaining strategies that yield Pareto security levels to the players or Pareto saddle points to the game, when they exist, are presented. Finally, we study games with more than two qualitative outcomes such as combat games. Using the notion of guaranteed outcomes, we obtain saddle-point solutions in mixed strategies for a number of cases. Examples illustrating the concepts, methods, and solutions are included.

Strategies for Rescheduling Tightly-Coupled Parallel Applications in Multi-Cluster Grids

As computational Grids are increasingly used for executing long running multi-phase parallel applications, it is important to develop efficient rescheduling frameworks that adapt application execution in response to resource and application dynamics. In this paper, three strategies or algorithms have been developed for deciding when and where to reschedule parallel applications that execute on multi-cluster Grids. The algorithms derive rescheduling plans that consist of potential points in application execution for rescheduling and schedules of resources for application execution between two consecutive rescheduling points. Using large number of simulations, it is shown that the rescheduling plans developed by the algorithms can lead to large decrease in application execution times when compared to executions without rescheduling on dynamic Grid resources. The rescheduling plans generated by the algorithms are also shown to be competitive when compared to the near-optimal plans generated by brute-force methods. Of the algorithms, genetic algorithm yielded the most efficient rescheduling plans with 9-12% smaller average execution times than the other algorithms.

Influence of the AgrC-AgrA Complex on the Response Time of Staphylococcus aureus Quorum Sensing

The Staphylococcus aureus agr quorum-sensing system plays a major role in the transition from the persistent to the virulent phenotype. S. aureus agr type I to IV strains are characterized by mutations in the sensor domain of the histidine kinase AgrC and differences in the sequences of the secreted autoinducing peptides (AIP). Here we demonstrate that interactions between the cytosolic domain of AgrC (AgrC(Cyto)) and the response regulator domain of AgrA (AgrA(RR)) dictate the spontaneity of the cellular response to AIP stimuli. The crystal structure of AgrC(Cyto) provided a basis for a mechanistic model of AgrC-AgrA interactions. This model enabled an analysis of the biochemical and biophysical parameters of AgrC-AgrA interactions in the context of the conformational features of the AgrC-AgrA complex. This analysis revealed distinct sequence and conformational features that determine the affinity, specificity, and kinetics of the phosphotransfer reaction. This step, which governs the response time for transcriptional reengineering triggered by an AIP stimulus, is independent of the agr type and similar for agonist and antagonist stimuli. These experimental data could serve as a basis on which to validate simulations of the quorum-sensing response and for strategies that employ the agr quorum-sensing system to combat biofilm formation in S. aureus infections.

Decentralized demand-supply matching using community microgrids and consumer demand response: A scenario analysis

Developing countries constantly face the challenge of reliably matching electricity supply to increasing consumer demand. The traditional policy decisions of increasing supply and reducing demand centrally, by building new power plants and/or load shedding, have been insufficient. Locally installed microgrids along with consumer demand response can be suitable decentralized options to augment the centralized grid based systems and plug the demand-supply gap. The objectives of this paper are to: (1) develop a framework to identify the appropriate decentralized energy options for demand supply matching within a community, and, (2) determine which of these options can suitably plug the existing demand-supply gap at varying levels of grid unavailability. A scenario analysis framework is developed to identify and assess the impact of different decentralized energy options at a community level and demonstrated for a typical urban residential community Vijayanagar, Bangalore in India. A combination of LPG based CHP microgrid and proactive demand response by the community is the appropriate option that enables the Vijayanagar community to meet its energy needs 24/7 in a reliable, cost-effective manner. The paper concludes with an enumeration of the barriers and feasible strategies for the implementation of community microgrids in India based on stakeholder inputs. (C) 2014 Elsevier Ltd. All rights reserved.

Predicting clinical response to anticancer drugs using an ex vivo platform that captures tumour heterogeneity

Predicting clinical response to anticancer drugs remains a major challenge in cancer treatment. Emerging reports indicate that the tumour microenvironment and heterogeneity can limit the predictive power of current biomarker-guided strategies for chemotherapy. Here we report the engineering of personalized tumour ecosystems that contextually conserve the tumour heterogeneity, and phenocopy the tumour microenvironment using tumour explants maintained in defined tumour grade-matched matrix support and autologous patient serum. The functional response of tumour ecosystems, engineered from 109 patients, to anticancer drugs, together with the corresponding clinical outcomes, is used to train a machine learning algorithm; the learned model is then applied to predict the clinical response in an independent validation group of 55 patients, where we achieve 100% sensitivity in predictions while keeping specificity in a desired high range. The tumour ecosystem and algorithm, together termed the CANScript technology, can emerge as a powerful platform for enabling personalized medicine.

Interplay of male traits, male mating strategies and female mate choice in the Asian elephant, Elephas maximus

Elaborate male traits with no apparent adaptive value may have evolved through female mate discrimination. Tusks are an elaborate male-only trait in the Asian elephant that could potentially influence female mate choice. We examined the effect of male body size, tusk possession and musth status on female mate choice in an Asian elephant population. Large/musth males received positive responses from oestrous females towards courtship significantly more often than did small/non-musth males. Young, tusked non-musth males attempted courtship significantly more often than their tuskless peers, and received more positive responses (though statistically insignificant) than did tuskless males. A positive response did not necessarily translate into mating because of mate-guarding by a dominant male. Female elephants appear to choose mates based primarily on traits such as musth that signal direct fertility benefits through increased sperm received than for traits such as tusks that may signal only indirect fitness benefits.