Automatic estimation of flux distributions of astrophysical source populations

In astrophysics a common goal is to infer the flux distribution of populations of scientifically interesting objects such as pulsars or supernovae. In practice, inference for the flux distribution is often conducted using the cumulative distribution of the number of sources detected at a given sensitivity. The resulting "$\log(N>S)$-$\log (S)$" relationship can be used to compare and evaluate theoretical models for source populations and their evolution. Under restrictive assumptions the relationship should be linear. In practice, however, when simple theoretical models fail, it is common for astrophysicists to use prespecified piecewise linear models. This paper proposes a methodology for estimating both the number and locations of "breakpoints" in astrophysical source populations that extends beyond existing work in this field. An important component of the proposed methodology is a new interwoven EM algorithm that computes parameter estimates. It is shown that in simple settings such estimates are asymptotically consistent despite the complex nature of the parameter space. Through simulation studies it is demonstrated that the proposed methodology is capable of accurately detecting structural breaks in a variety of parameter configurations. This paper concludes with an application of our methodology to the Chandra Deep Field North (CDFN) data set.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS750 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Derivation of genetic interaction networks from quantitative phenotype data

We have generalized the derivation of genetic-interaction networks from quantitative phenotype data. Familiar and unfamiliar modes of genetic interaction were identified and defined. A network was derived from agar-invasion phenotypes of mutant yeast. Mutations showed specific modes of genetic interaction with specific biological processes. Mutations formed cliques of significant mutual information in their large-scale patterns of genetic interaction. These local and global interaction patterns reflect the effects of gene perturbations on biological processes and pathways

Variation in Vital-rate Sensitivity Between Populations of Texas Horned Lizards

Demographic studies of imperiled populations can aid managers in planning conservation actions. However, applicability of findings for a single population across a species’ range is sometimes questionable. We conducted long-term studies (8 and 9 years, respectively) of 2 populations of the lizard Phrynosoma cornutum separated by 1000 km within the historical distribution of the species. The sites were a 15-ha urban wildlife reserve on Tinker Air Force Base (TAFB) in central Oklahoma and a 6000-ha wildland site in southern Texas, the Chaparral Wildlife Management Area (CWMA). We predicted a trade-off between the effect of adult survival and fecundity on population growth rate (λ), leading to population-specific contributions of individual vital rates to λ and individualized strategies for conservation and management of this taxon. The CWMA population had lower adult survival and higher fecundity than TAFB. As predicted, there was a trade-off in the effects of adult survival and fecundity on λ between the two sites; fecundity affected λ more at CWMA than at TAFB. However, adult survival had the smallest effect on λ in both populations. We found that recruitment in P. cornutum most affected λ at both sites, with hatchling survival having the strongest influence on λ. Management strategies focusing on hatchling survival would strongly benefit both populations. As a consequence, within the constraint of the need to more accurately estimate hatchling survival, managers across the range of species such as P. cornutum could adopt similar management priorities with respect to stage classes, despite intra-population differences in population vital rates

Concept of an Upright Wearable Positron Emission Tomography Imager in Humans

Background: Positron Emission Tomography (PET) is traditionally used to image patients in restrictive positions, with few devices allowing for upright, brain-dedicated imaging. Our team has explored the concept of wearable PET imagers which could provide functional brain imaging of freely moving subjects. To test feasibility and determine future considerations for development, we built a rudimentary proof-of-concept prototype (Helmet_PET) and conducted tests in phantoms and four human volunteers. Methods: Twelve Silicon Photomultiplier-based detectors were assembled in a ring with exterior weight support and an interior mechanism that could be adjustably fitted to the head. We conducted brain phantom tests as well as scanned four patients scheduled for diagnostic F18-FDG PET/CT imaging. For human subjects the imager was angled such that field of view included basal ganglia and visual cortex to test for typical resting-state pattern. Imaging in two subjects was performed ~4 hr after PET/CT imaging to simulate lower injected F18-FDG dose by taking advantage of the natural radioactive decay of the tracer (F18 half-life of 110 min), with an estimated imaging dosage of 25% of the standard. Results: We found that imaging with a simple lightweight ring of detectors was feasible using a fraction of the standard radioligand dose. Activity levels in the human participants were quantitatively similar to standard PET in a set of anatomical ROIs. Typical resting-state brain pattern activation was demonstrated even in a 1 min scan of active head rotation. Conclusion: To our knowledge, this is the first demonstration of imaging a human subject with a novel wearable PET imager that moves with robust head movements. We discuss potential research and clinical applications that will drive the design of a fully functional device. Designs will need to consider trade-offs between a low weight device with high mobility and a heavier device with greater sensitivity and larger field of view

Towards Symbolic Model-Based Mutation Testing: Combining Reachability and Refinement Checking

Model-based mutation testing uses altered test models to derive test cases that are able to reveal whether a modelled fault has been implemented. This requires conformance checking between the original and the mutated model. This paper presents an approach for symbolic conformance checking of action systems, which are well-suited to specify reactive systems. We also consider nondeterminism in our models. Hence, we do not check for equivalence, but for refinement. We encode the transition relation as well as the conformance relation as a constraint satisfaction problem and use a constraint solver in our reachability and refinement checking algorithms. Explicit conformance checking techniques often face state space explosion. First experimental evaluations show that our approach has potential to outperform explicit conformance checkers.Comment: In Proceedings MBT 2012, arXiv:1202.582