Discovery of the brightest T dwarf in the northern hemisphere

We report the discovery of a bright (H=12.77) brown dwarf designated SIMP J013656.5+093347. The discovery was made as part of a near-infrared proper motion survey, SIMP (Sondage Infrarouge de Mouvement Propre), which uses proper motion and near-infrared/optical photometry to identify brown dwarf candidates. A low resolution (lambda/dlambda~40) spectrum of this brown dwarf covering the 0.88-2.35 microns wavelength interval is presented. Analysis of the spectrum indicates a spectral type of T2.5+/-0.5. A photometric distance of 6.4+/-0.3 pc is estimated assuming it is a single object. Current observations rule out a binary of mass ratio ~1 and separation >5 AU. SIMP 0136 is the brightest T dwarf in the northern hemisphere and is surpassed only by Eps Indi Bab over the whole sky. It is thus an excellent candidate for detailed studies and should become a benchmark object for the early-T spectral class.Comment: 4 pages, 3 figures, To be published in November 1, 2006 issue of ApJL. Following IAU recommendation, the survey acronym (IBIS) was changed to SIM

Notes on Captive Sea Otters

Notes on the behaviour of three yearlings kept two and a half months in 1954 in a dry environment at Amchitka in the Aleutians. Their sleeping, preening, reaction to man and feeding habits, drinking, locomotion, handling, food and sociability voice, etc., are discussed in detail. Their anatomy and environment in captivity are also discussed: water for swimming was found desirable, if not necessary. Results of physiological investigations are reported by D.E. Stullken and C.M. Kirkpatrick, q.v

Clustering of solutions in the random satisfiability problem

Using elementary rigorous methods we prove the existence of a clustered phase in the random $K$-SAT problem, for $K\geq 8$. In this phase the solutions are grouped into clusters which are far away from each other. The results are in agreement with previous predictions of the cavity method and give a rigorous confirmation to one of its main building blocks. It can be generalized to other systems of both physical and computational interest.Comment: 4 pages, 1 figur

Synthesizing and tuning chemical reaction networks with specified behaviours

We consider how to generate chemical reaction networks (CRNs) from functional specifications. We propose a two-stage approach that combines synthesis by satisfiability modulo theories and Markov chain Monte Carlo based optimisation. First, we identify candidate CRNs that have the possibility to produce correct computations for a given finite set of inputs. We then optimise the reaction rates of each CRN using a combination of stochastic search techniques applied to the chemical master equation, simultaneously improving the of correct behaviour and ruling out spurious solutions. In addition, we use techniques from continuous time Markov chain theory to study the expected termination time for each CRN. We illustrate our approach by identifying CRNs for majority decision-making and division computation, which includes the identification of both known and unknown networks.Comment: 17 pages, 6 figures, appeared the proceedings of the 21st conference on DNA Computing and Molecular Programming, 201

Crawford, Davis & the Right of Confrontation: Where Do We Go from Here?

Afternoon Panel Discussio

Computational statistics using the Bayesian Inference Engine

This paper introduces the Bayesian Inference Engine (BIE), a general parallel, optimised software package for parameter inference and model selection. This package is motivated by the analysis needs of modern astronomical surveys and the need to organise and reuse expensive derived data. The BIE is the first platform for computational statistics designed explicitly to enable Bayesian update and model comparison for astronomical problems. Bayesian update is based on the representation of high-dimensional posterior distributions using metric-ball-tree based kernel density estimation. Among its algorithmic offerings, the BIE emphasises hybrid tempered MCMC schemes that robustly sample multimodal posterior distributions in high-dimensional parameter spaces. Moreover, the BIE is implements a full persistence or serialisation system that stores the full byte-level image of the running inference and previously characterised posterior distributions for later use. Two new algorithms to compute the marginal likelihood from the posterior distribution, developed for and implemented in the BIE, enable model comparison for complex models and data sets. Finally, the BIE was designed to be a collaborative platform for applying Bayesian methodology to astronomy. It includes an extensible object-oriented and easily extended framework that implements every aspect of the Bayesian inference. By providing a variety of statistical algorithms for all phases of the inference problem, a scientist may explore a variety of approaches with a single model and data implementation. Additional technical details and download details are available from http://www.astro.umass.edu/bie. The BIE is distributed under the GNU GPL.Comment: Resubmitted version. Additional technical details and download details are available from http://www.astro.umass.edu/bie. The BIE is distributed under the GNU GP

The statistical mechanics of complex signaling networks : nerve growth factor signaling

It is becoming increasingly appreciated that the signal transduction systems used by eukaryotic cells to achieve a variety of essential responses represent highly complex networks rather than simple linear pathways. While significant effort is being made to experimentally measure the rate constants for individual steps in these signaling networks, many of the parameters required to describe the behavior of these systems remain unknown, or at best, estimates. With these goals and caveats in mind, we use methods of statistical mechanics to extract useful predictions for complex cellular signaling networks. To establish the usefulness of our approach, we have applied our methods towards modeling the nerve growth factor (NGF)-induced differentiation of neuronal cells. Using our approach, we are able to extract predictions that are highly specific and accurate, thereby enabling us to predict the influence of specific signaling modules in determining the integrated cellular response to the two growth factors. We show that extracting biologically relevant predictions from complex signaling models appears to be possible even in the absence of measurements of all the individual rate constants. Our methods also raise some interesting insights into the design and possible evolution of cellular systems, highlighting an inherent property of these systems wherein particular ''soft'' combinations of parameters can be varied over wide ranges without impacting the final output and demonstrating that a few ''stiff'' parameter combinations center around the paramount regulatory steps of the network. We refer to this property -- which is distinct from robustness -- as ''sloppiness.''Comment: 24 pages, 10 EPS figures, 1 GIF (makes 5 multi-panel figs + caption for GIF), IOP style; supp. info/figs. included as brown_supp.pd

Lack of association between COMT gene and deficit/nondeficit schizophrenia

BACKGROUND: The dopamine dysregulation hypothesis of schizophrenia posits that positive, negative and cognitive symptoms correlate with cortical/subcortical imbalances in dopaminergic transmission. A functional polymorphism (Val(158)Met) in the catechol-O-methyltransferase (COMT) gene is implicated in the pathophysiology of schizophrenia by its effect on prefrontal dopamine transmission, and its unique impact on prefrontal cognitive and behavioral phenotypes. Cognitive impairments and negative symptoms in schizophrenia have been hypothesized to be associated with hypodopaminergic states. Schizophrenia patients with the deficit syndrome are characterized by primary enduring negative symptoms, impairment on neurocognitive tasks sensitive to frontal and parietal cortical functioning, and poorer functional outcome compared to non-deficit patients. METHODS: Eighty-six schizophrenia cases that met DSM-IV criteria for schizophrenia were recruited. Additional categorization into deficit and nondeficit syndrome was performed using the Schedule for the Deficit Syndrome (SDS). A healthy comparison group (n = 50) matched to cases on age and ethnicity was recruited. Allele and genotype frequencies of the Val(158)Met polymorphism were compared among healthy controls, and schizophrenia cases with the deficit (n = 21), and nondeficit syndrome (n = 65). RESULTS: There was a significant difference in Val/Val genotype frequencies between schizophrenia cases (combined deficit/nondeficit) and healthy controls (p = 0.004). No significant differences in allele or genotype frequencies were observed between deficit and nondeficit cases. CONCLUSION: Results from this preliminary analysis failed to show an effect of COMT gene on deficit schizophrenia