Finished Genome Sequence of the Indole-3-Acetic Acid-Catabolizing Bacterium Pseudomonas putida 1290.

Use of indole-3-acetic acid (IAA) as a carbon, nitrogen, and energy source by Pseudomonas putida 1290 is linked to the possession of a gene cluster that codes for conversion to catechol. Here, we present the genomic context of this iac gene cluster, which includes genes for IAA chemotaxis/transport and catechol catabolism

Facing fear: Expression of fear facilitates processing of emotional information

Evidence shows that manipulating the expressive component of fear can influence the processing of emotional information. Participants unobtrusively produced the expressive behaviors typical of fear, anger or happiness. Participants producing the expression of fear were faster at classifying verbal material with emotional content than participants producing the expressions of happiness or anger. These effects were especially pronounced for participants who were generally sensitive to their own bodily cues, as indicated by their degree of field-dependence measured by the Rod-and-Frame Task (Witkin &amp; Asch, 1948). The results suggest that one way of eliciting the cognitive consequences of fear is by inducing the embodied expressive behavior.</jats:p

Flexibly Instructable Agents

This paper presents an approach to learning from situated, interactive tutorial instruction within an ongoing agent. Tutorial instruction is a flexible (and thus powerful) paradigm for teaching tasks because it allows an instructor to communicate whatever types of knowledge an agent might need in whatever situations might arise. To support this flexibility, however, the agent must be able to learn multiple kinds of knowledge from a broad range of instructional interactions. Our approach, called situated explanation, achieves such learning through a combination of analytic and inductive techniques. It combines a form of explanation-based learning that is situated for each instruction with a full suite of contextually guided responses to incomplete explanations. The approach is implemented in an agent called Instructo-Soar that learns hierarchies of new tasks and other domain knowledge from interactive natural language instructions. Instructo-Soar meets three key requirements of flexible instructability that distinguish it from previous systems: (1) it can take known or unknown commands at any instruction point; (2) it can handle instructions that apply to either its current situation or to a hypothetical situation specified in language (as in, for instance, conditional instructions); and (3) it can learn, from instructions, each class of knowledge it uses to perform tasks.Comment: See http://www.jair.org/ for any accompanying file

Fresh-Register Automata

What is a basic automata-theoretic model of computation with names and fresh-name generation? We introduce Fresh-Register Automata (FRA), a new class of automata which operate on an infinite alphabet of names and use a finite number of registers to store fresh names, and to compare incoming names with previously stored ones. These finite machines extend Kaminski and Francez’s Finite-Memory Automata by being able to recognise globally fresh inputs, that is, names fresh in the whole current run. We exam-ine the expressivity of FRA’s both from the aspect of accepted languages and of bisimulation equivalence. We establish primary properties and connections between automata of this kind, and an-swer key decidability questions. As a demonstrating example, we express the theory of the pi-calculus in FRA’s and characterise bisimulation equivalence by an appropriate, and decidable in the finitary case, notion in these automata

The X-ray luminosity function of AGN at z~3

We combine Lyman-break colour selection with ultradeep (> 200 ks) Chandra X-ray imaging over a survey area of ~0.35 deg^2 to select high redshift AGN. Applying careful corrections for both the optical and X-ray selection functions, the data allow us to make the most accurate determination to date of the faint end of the X-ray luminosity function (XLF) at z~3. Our methodology recovers a number density of X-ray sources at this redshift which is at least as high as previous surveys, demonstrating that it is an effective way of selecting high z AGN. Comparing to results at z=1, we find no evidence that the faint slope of the XLF flattens at high z, but we do find significant (factor ~3.6) negative evolution of the space density of low luminosity AGN. Combining with bright end data from very wide surveys we also see marginal evidence for continued positive evolution of the characteristic break luminosity L*. Our data therefore support models of luminosity-dependent density evolution between z=1 and z=3. A sharp upturn in the the XLF is seen at the very lowest luminosities (Lx < 10^42.5 erg s^-1), most likely due to the contribution of pure X-ray starburst galaxies at very faint fluxes.Comment: 16 pages, 9 figures, accepted for publication in MNRA

Scale-freeness for networks as a degenerate ground state: A Hamiltonian formulation

The origin of scale-free degree distributions in the context of networks is addressed through an analogous non-network model in which the node degree corresponds to the number of balls in a box and the rewiring of links to balls moving between the boxes. A statistical mechanical formulation is presented and the corresponding Hamiltonian is derived. The energy, the entropy, as well as the degree distribution and its fluctuations are investigated at various temperatures. The scale-free distribution is shown to correspond to the degenerate ground state, which has small fluctuations in the degree distribution and yet a large entropy. We suggest an implication of our results from the viewpoint of the stability in evolution of networks.Comment: 7 pages, 3 figures. To appear in Europhysics lette

X-ray properties of UV-selected star forming galaxies at z~1 in the Hubble Deep Field North

We present an analysis of the X-ray emission from a large sample of ultraviolet (UV) selected, star forming galaxies with 0.74<z<1.32 in the Hubble Deep Field North (HDF-N) region. By excluding all sources with significant detected X-ray emission in the 2 Ms Chandra observation we are able to examine the properties of galaxies for which the emission in both UV and X-ray is expected to be predominantly due to star formation. Stacking the X-ray flux from 216 galaxies in the soft and hard bands produces significant detections. The derived mean 2-10 keV rest-frame luminosity is 2.97+/-0.26x10^(40) erg/s, corresponding to an X-ray derived star formation rate (SFR) of 6.0+/-0.6 Msolar/yr. Comparing the X-ray value with the mean UV derived SFR, uncorrected for attenuation, we find that the average UV attenuation correction factor is \~3. By binning the galaxy sample according to UV magnitude and colour, correlations between UV and X-ray emission are also examined. We find a strong positive correlation between X-ray emission and rest-frame UV emission. A correlation between the ratio of X-ray-to-UV emission and UV colour is also seen, such that L(X)/L(UV) increases for redder galaxies. Given that X-ray emission offers a view of star formation regions that is relatively unaffected by extinction, results such as these can be used to evaluate the effects of dust on the UV emission from high-z galaxies. For instance we derive a relationship for estimating UV attenuation corrections as a function of colour excess. The observed relation is inconsistent with the Calzetti et al. (2000) reddening law which over predicts the range in UV attenuation corrections by a factor of ~100 for the UV selected z~1 galaxies in this sample (abridged).Comment: 10 pages, 7 figures, accepted for publication in MNRA