Approximate knowledge of rationality and correlated equilibria

We extend Aumann's [3] theorem deriving correlated equilibria as a consequence of common priors and common knowledge of rationality by explicitly allowing for non-rational behavior. We replace the assumption of common knowledge of rationality with a substantially weaker notion, joint p-belief of rationality, where agents believe the other agents are rational with probabilities p = (pi)i2I or more. We show that behavior in this case constitutes a constrained correlated equilibrium of a doubled game satisfying certain p-belief constraints and characterize the topological structure of the resulting set of p-rational outcomes. We establish continuity in the parameters p and show that, for p su ciently close to one, the p-rational outcomes are close to the correlated equilibria and, with high probability, supported on strategies that survive the iterated elimination of strictly dominated strategies. Finally, we extend Aumann and Dreze's [4] theorem on rational expectations of interim types to the broader p-rational belief systems, and also discuss the case of non-common priors.

THE ISOLATION, CHARACTERIZATION AND OXIDATION REACTION OF ACTIVE INTERMEDIATES OF CYTOCHROME-P-450 MODEL SYSTEM OXOCHROMIUM(V) TETRAPHENYLPORPHYRIN COMPLEXES

Oxochromium (V) tetraphenylporphyrin complexes, O = Cr (V) TPP (Cl) PhI. O = Cr-(V) TPP (N3) PhI and O = Cr (V)TPP (p-CH3OC6H4O)1/2PhI were isolated from the reaction of Cr (III) TPP (Cl). Cr (III) TPP (N3) Py or Cr (III) TPP (p-CH3OC6H4O) THF with iodosy

Automated P.falciparum detection system for post-treatment malaria diagnosis using modified annular ring ratio method

The gametocytes of the malaria parasite Plasmodium falciparum are highly resistant to antimalarial drugs. Its presence in the blood can be detected even after a successful malaria treatment. This paper explains a modified Annular Ring Ratio method which successfully locates and differentiates gametocytes of P. falciparum species in thin blood film images. The method can be used as an efficient tool for gametocyte detection for post-treatment malaria diagnosis. It also identifies the presence of any White Blood Cells (WBCs) in the image, and discards other artifacts and non infected cells. It utilizes the information based on structure, color and geometry of the cells and does not require any segmentation or non-illumination correction techniques that are commonly used for cell detection.

NMR structural study on the As-P-S glassy system

Glasses having the composition As2S3(1-x)-P2S5(x) with x ranging from 0 to 0.7 have been investigated to determine the compositional effect on properties and local structure. Glass transition temperature (T,) decreases and molar volume (V,,) increases with an increase in P content. Using P-31 NMR, we measured the strength of the P-31-P-31 magnetic dipolar interaction in the glass samples and the AsPS4 crystallized phase. Based on these data, we observed the formation of the As2P2S8 network, which reflects an increase in the average coordination number and a decrease in the degree of rigidity.

Optimal power system stabilizer tuning in multi-machine system via an improved differential evolution

Power system stabilizer (PSS) is one of the most important controllers in modern power systems for damping low frequency oscillations. Many efforts have been dedicated to design the tuning methodologies and allocation techniques to obtain optimal damping behaviors of the system. Traditionally, it is tuned mostly for local damping performance, however, in order to obtain a globally optimal performance, the tuning of PSS needs to be done considering more variables. Furthermore, with the enhancement of system interconnection and the increase of system complexity, new tools are required to achieve global tuning and coordination of PSS to achieve optimal solution in a global meaning. Differential evolution (DE) is a recognized as a simple and powerful global optimum technique, which can gain fast convergence speed as well as high computational efficiency. However, as many other evolutionary algorithms (EA), the premature of population restricts optimization capacity of DE. In this paper, a modified DE is proposed and applied for optimal PSS tuning of 39-Bus New-England system. New operators are introduced to reduce the probability of getting premature. To investigate the impact of system conditions on PSS tuning, multiple operating points will be studied. Simulation result is compared with standard DE and particle swarm optimization (PSO).

Power system sensitivity analysis considering induction motor loads

Power system operation and planning are facing increasing uncertainties especially with the deregulation process and increasing demand for power. Probabilistic power system stability assessment and probabilistic power system planning have been identified by EPRI as one of the important trends in power system operations and planning. Probabilistic small signal stability assessment studies the impact of system parameter uncertainties on system small disturbance stability characteristics. Researches in this area have covered many uncertainties factors such as controller parameter uncertainties and generation uncertainties. One of the most important factors in power system stability assessment is load dynamics. In this paper, composite load model is used to consider the uncertainties from load parameter uncertainties impact on system small signal stability characteristics. The results provide useful insight into the significant stability impact brought to the system by load dynamics. They can be used to help system operators in system operation and planning analysis.

Activation of toxic chemicals by cytochrome P450 enzymes : regio- and stereoselective oxidation of aflatoxin B1

Cytochrome P450 (P450) enzymes are involved in the oxidations of numerous steroids, eicosanoids, alkaloids, and other endogenous substrates. These enzymes are also the major ones involved in the oxidation of potential toxicants and carcinogens such as those encountered among pollutants, solvents, and pesticides, as well as many natural products. A proper understanding of the basic mechanisms by which the P450 enzymes oxidize such compounds is important in developing rational strategies for the evaluation of the risks of these compounds.

Influence of cytochrome P-450 inhibitors on the inhalative uptake of methyl chloride and methylene chloride in male B6C3F1 mice

Dichloromethane (DCM) is thought to be metabolized in vivo by two independent pathways: a glutathione (GSH) dependent pathway that yields CO2 and a cytochrome P-450 mediated one that yields both CO and CO2 (Gargas et al 1986). With a physiologically based pharmacokinetic (PB-PK) model, Andersen et al (1987) calculate the quantitative parameters for both metabolic pathways. Using the kinetic parameters thus obtained and the results of two carcinogenicity studies with rodents (Serota et al 1986; NTP 1985), the authors then estimate the tumour risk for humans.

Topological phases, Majorana modes and quench dynamics in a spin ladder system

We explore the salient features of the `Kitaev ladder', a two-legged ladder version of the spin-1/2 Kitaev model on a honeycomb lattice, by mapping it to a one-dimensional fermionic p-wave superconducting system. We examine the connections between spin phases and topologically non-trivial phases of non-interacting fermionic systems, demonstrating the equivalence between the spontaneous breaking of global Z(2) symmetry in spin systems and the existence of isolated Majorana modes. In the Kitaev ladder, we investigate topological properties of the system in different sectors characterized by the presence or absence of a vortex in each plaquette of the ladder. We show that vortex patterns can yield a rich parameter space for tuning into topologically non-trivial phases. We introduce and employ a new topological invariant for explicitly determining the presence of zero energy Majorana modes at the boundaries of such phases. Finally, we discuss dynamic quenching between topologically non-trivial phases in the Kitaev ladder and, in particular, the post-quench dynamics governed by tuning through a quantum critical point.

Robust Control of Evolutionary Dynamics

The application of principles from evolutionary biology has long been used to gain new insights into the progression and clinical control of both infectious diseases and neoplasms. This iterative evolutionary process consists of expansion, diversification and selection within an adaptive landscape - species are subject to random genetic or epigenetic alterations that result in variations; genetic information is inherited through asexual reproduction and strong selective pressures such as therapeutic intervention can lead to the adaptation and expansion of resistant variants. These principles lie at the center of modern evolutionary synthesis and constitute the primary reasons for the development of resistance and therapeutic failure, but also provide a framework that allows for more effective control.

A model system for studying the evolution of resistance and control of therapeutic failure is the treatment of chronic HIV-1 infection by broadly neutralizing antibody (bNAb) therapy. A relatively recent discovery is that a minority of HIV-infected individuals can produce broadly neutralizing antibodies, that is, antibodies that inhibit infection by many strains of HIV. Passive transfer of human antibodies for the prevention and treatment of HIV-1 infection is increasingly being considered as an alternative to a conventional vaccine. However, recent evolution studies have uncovered that antibody treatment can exert selective pressure on virus that results in the rapid evolution of resistance. In certain cases, complete resistance to an antibody is conferred with a single amino acid substitution on the viral envelope of HIV.

The challenges in uncovering resistance mechanisms and designing effective combination strategies to control evolutionary processes and prevent therapeutic failure apply more broadly. We are motivated by two questions: Can we predict the evolution to resistance by characterizing genetic alterations that contribute to modified phenotypic fitness? Given an evolutionary landscape and a set of candidate therapies, can we computationally synthesize treatment strategies that control evolution to resistance?

To address the first question, we propose a mathematical framework to reason about evolutionary dynamics of HIV from computationally derived Gibbs energy fitness landscapes -- expanding the theoretical concept of an evolutionary landscape originally conceived by Sewall Wright to a computable, quantifiable, multidimensional, structurally defined fitness surface upon which to study complex HIV evolutionary outcomes.

To design combination treatment strategies that control evolution to resistance, we propose a methodology that solves for optimal combinations and concentrations of candidate therapies, and allows for the ability to quantifiably explore tradeoffs in treatment design, such as limiting the number of candidate therapies in the combination, dosage constraints and robustness to error. Our algorithm is based on the application of recent results in optimal control to an HIV evolutionary dynamics model and is constructed from experimentally derived antibody resistant phenotypes and their single antibody pharmacodynamics. This method represents a first step towards integrating principled engineering techniques with an experimentally based mathematical model in the rational design of combination treatment strategies and offers predictive understanding of the effects of combination therapies of evolutionary dynamics and resistance of HIV. Preliminary in vitro studies suggest that the combination antibody therapies predicted by our algorithm can neutralize heterogeneous viral populations despite containing resistant mutations.