Properties of the non-Gaussian fixed point in 4D compact U(1) lattice gauge theory

We examine selected properties of the gauge-ball spectrum and fermionic variables in the vicinity of the recently discussed non-Gaussian fixed point of 4D compact U(1) lattice gauge theory within the quenched approximation. Approaching the critical point from within the confinement phase, our data support scaling of $T1^{+-}$ gauge-ball states in units of the string tension square root. The analysis of the chiral condensate within the framework of a scaling form for the equation of state suggests non mean-field values for the magnetic exponents $\delta$ and $\beta_{exp}$.Comment: 73K postscript fil

Universality of the gauge-ball spectrum of the four-dimensional pure U(1) gauge theory

We continue numerical studies of the spectrum of the pure U(1) lattice gauge theory in the confinement phase, initiated in our previous work. Using the extended Wilson action $S = -\sum_P [\beta \cos(\Theta_P) + \gamma \cos(2\Theta_P)]$ we address the question of universality of the phase transition line in the ($\beta,\gamma$) plane between the confinement and the Coulomb phases. Our present results at $\gamma= -0.5$ for the gauge-ball spectrum are fully consistent with the previous results obtained at $\gamma= -0.2$. Again, two different correlation length exponents, $\nu_{ng} = 0.35(3)$ and $\nu_{g} = 0.49(7)$, are obtained in different channels. We also confirm the stability of the values of these exponents with respect to the variation of the distance from the critical point at which they are determined. These results further demonstrate universal critical behaviour of the model at least up to correlation lengths of 4 lattice spacings when the phase transition is approached in some interval at $\gamma\leq -0.2$.Comment: 16 page

On the Joint Distribution of Energy Levels of Random Schroedinger Operators

We consider operators with random potentials on graphs, such as the lattice version of the random Schroedinger operator. The main result is a general bound on the probabilities of simultaneous occurrence of eigenvalues in specified distinct intervals, with the corresponding eigenfunctions being separately localized within prescribed regions. The bound generalizes the Wegner estimate on the density of states. The analysis proceeds through a new multiparameter spectral averaging principle

Salivary Cortisol Mediates Effects of Poverty and Parenting on Executive Functions in Early Childhood

In a predominantly low-income population-based longitudinal sample of 1,292 children followed from birth, higher level of salivary cortisol assessed at ages 7, 15, and 24 months was uniquely associated with lower executive function ability and to a lesser extent IQ at age 3 years. Measures of positive and negative aspects of parenting and household risk were also uniquely related to both executive functions and IQ. The effect of positive parenting on executive functions was partially mediated through cortisol. Typical or resting level of cortisol was increased in African American relative to White participants. In combination with positive and negative parenting and household risk, cortisol mediated effects of African American ethnicity, income-to-need, and maternal education on child cognitive ability.

Toward Meta-level Control of Autonomous Agents

AbstractMetareasoning is an important capability for autonomous systems, particularly for those being deployed on long duration missions. An agent with increased self-observation and the ability to control itself in response to changing environments will be more capable in achieving its goals. This is essential for long-duration missions where system designers will not be able to, theoretically or practically, predict all possible problems that the agent may encounter. In this paper we describe preliminary work that integrates the metacognitive architecture MIDCA with an autonomous TREX agent, creating a more self-observable and adaptive agent

Evasion of autophagy mediated by Rickettsia surface protein OmpB is critical for virulence.

Rickettsia are obligate intracellular bacteria that evade antimicrobial autophagy in the host cell cytosol by unknown mechanisms. Other cytosolic pathogens block different steps of autophagy targeting, including the initial step of polyubiquitin-coat formation. One mechanism of evasion is to mobilize actin to the bacterial surface. Here, we show that actin mobilization is insufficient to block autophagy recognition of the pathogen Rickettsia parkeri. Instead, R. parkeri employs outer membrane protein B (OmpB) to block ubiquitylation of the bacterial surface proteins, including OmpA, and subsequent recognition by autophagy receptors. OmpB is also required for the formation of a capsule-like layer. Although OmpB is dispensable for bacterial growth in endothelial cells, it is essential for R. parkeri to block autophagy in macrophages and to colonize mice because of its ability to promote autophagy evasion in immune cells. Our results indicate that OmpB acts as a protective shield to obstruct autophagy recognition, thereby revealing a distinctive bacterial mechanism to evade antimicrobial autophagy

MIDCA: A Metacognitive, Integrated Dual-Cycle Architecture for Self-Regulated Autonomy

This report documents research performed under ONR grant N000141210172 for the period 1 June 2012 through 31 May 2013. The goals of this research are to provide a sound theoretical understanding of the role of metacognition in cognitive architectures and to demonstrate the underlying theory through implemented computational models. During the last year, the team has been integrating existing implemented systems to form an initial architectural structure that approximates the major functions of MIDCA. These include the SHOP2 hierarchical planning system and the Meta-AQUA integrated multistrategy learning system. We have also produced substantial progress on the data-driven track of the interpretation procedure. Last year’s work on using the A-distance metric for anomaly detection has been matured, and we have collected substantial observations used in empirical evaluation. Additionally we started implementation of a neural network to induce proto-type nodes for observed anomalies, and we are developing methods to prioritize explanations and responses that have proven effective with past anomalies in proto-type categories. The data are encouraging and the research community has reacted favorably. Several new publications support our claims herein

Clashes in the Infosphere, General Intelligence, and Metacognition: Final project report

Humans confront the unexpected every day, deal with it, and often learn from it. AI agents, on the other hand, are typically brittle—they tend to break down as soon as something happens for which their creators did not explicitly anticipate. The central focus of our research project is this problem of brittleness which may also be the single most important problem facing AI research. Our approach to brittleness is to model a common method that humans use to deal with the unexpected, namely to note occurrences of the unexpected (i.e., anomalies), to assess any problem signaled by the anomaly, and then to guide a response or solution that resolves it. The result is the Note-Assess-Guide procedure of what we call the Metacognitive Loop or MCL. To do this, we have implemented MCL-based systems that enable agents to help themselves; they must establish expectations and monitor them, note failed expectations, assess their causes, and then choose appropriate responses. Activities for this project have developed and refined a human-dialog agent and a robot navigation system to test the generality of this approach