Research and education in management of large-scale technical programs

A research effort is reported which was conducted by NASA in conjunction with Drexel University, and which was aimed at an improved understanding of large scale systems technology and management

Laser-induced solid-solid phase transition in As under pressure: A theoretical prediction

In Arsenic a pressure-induced solid-solid phase transition from the A7 into the simple cubic structure has been experimentally demonstrated [Beister et al., Phys. Rev. B 41, 5535 (1990)]. In this paper we present calculations, which predict that this phase transition can also be induced by an ultrashort laser pulse in As under pressure. In addition, calculations for the pressure-induced phase transition are presented. Using density functional theory in the generalized gradient approximation, we found that the pressure-induced phase transition takes place at 26.3 GPa and is accompanied by a volume change "Delta V" = 0.5 bohr^3/atom. The laser-induced phase transition is predicted for an applied pressure of 23.8 GPa and an absorbed laser energy of 2.8 mRy/atom.Comment: 9 pages, 5 figures Changes to content To be published in New Journal of Physics (accepted for publication

Pre- and post-operative cerebral blood flow changes in subarachnoid haemorrhage

Assessment of cerebral perfusion on patients with subarachnoid haemorrhage (SAH) in the Neurologic Intensive Care Unit is difficult since nuclear medicine imaging modalities capable of measuring cerebral blood flow (CBF) are not generally available. We performed 101 quantitative (ml/100g-min) bedside CBF measurements on 40 individual patients to correlate SAH grade with CBF and to assess the effect of surgical intervention on CBF. Global CBF (G-CBF) and bihemispheric CBF (B-CBF) asymmetry were correlated with the grade of SAH pre- and post-operatively.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41645/1/701_2005_Article_BF01405693.pd

Exploring children’s perspectives on the welfare needs of pet animals

This work was supported by the Department for Environment, Food and Rural Affairs (grant number AW1404).Children are increasingly viewed as important recipients of eduational interventions to improve animal welfare, yet research examining their perspectives is lacking, particularly within the UK. Helping children to care appropriately for animals depends, not least, on an ability to understand the needs of different species and correctly identify cues given by the animal that indicate its welfare state. This study began to explore: (a) children’s perceptions of welfare needs, focusing on four common pet animals; (b) influences on the development of knowledge; (c) beliefs about whether or not (all) animals are sentient, and (d) their confidence in identifying when their own pets are in need. Fourteen focus groups were carried out with 53 children aged 7 to 13 years. Findings highlighted an affirmative response that animals have feelings (dogs especially), albeit with doubts about this applying universally. There was wide variation in children’s knowledge of welfare needs, even among owners of the animal in question. Conversely, some children lacked confidence in spite of the extensive knowledge they had developed through direct experience. An important finding was a perceived difficulty in identifying the needs of particular species or specific types of need in their own pets. Fitting well with a recent emphasis on “positive welfare,” children felt that many animals need demonstrative love and attention, especially cats and dogs. While there is clearly scope for educating children about common needs and cues that indicate animals’ welfare state, other areas pose a greater challenge. Emotional connection seems important in the development of extensive knowledge and concern for welfare. Accordingly, animals that do not possess the kind of behavioral repertoire that is easy to interpret or allows for a perceived sense of reciprocity are possibly at risk of negative welfare experiences.PostprintPeer reviewe

Automatic differentiation for gradient-based optimization of radiatively heated microelectronics manufacturing equipment

Automatic differentiation is applied to the optimal design of microelectronic manufacturing equipment. The performance of nonlinear, least-squares optimization methods is compared between numerical and analytical gradient approaches. The optimization calculations are performed by running large finite-element codes in an object-oriented optimization environment. The Adifor automatic differentiation tool is used to generate analytic derivatives for the finite-element codes. The performance results support previous observations that automatic differentiation becomes beneficial as the number of optimization parameters increases. The increase in speed, relative to numerical differences, has a limited value and results are reported for two different analysis codes

A New Approach to Searching for Dark Matter Signals in Fermi-LAT Gamma Rays

Several cosmic ray experiments have measured excesses in electrons and positrons, relative to standard backgrounds, for energies from ~ 10 GeV - 1 TeV. These excesses could be due to new astrophysical sources, but an explanation in which the electrons and positrons are dark matter annihilation or decay products is also consistent. Fortunately, the Fermi-LAT diffuse gamma ray measurements can further test these models, since the electrons and positrons produce gamma rays in their interactions in the interstellar medium. Although the dark matter gamma ray signal consistent with the local electron and positron measurements should be quite large, as we review, there are substantial uncertainties in the modeling of diffuse backgrounds and, additionally, experimental uncertainties that make it difficult to claim a dark matter discovery. In this paper, we introduce an alternative method for understanding the diffuse gamma ray spectrum in which we take the intensity ratio in each energy bin of two different regions of the sky, thereby canceling common systematic uncertainties. For many spectra, this ratio fits well to a power law with a single break in energy. The two measured exponent indices are a robust discriminant between candidate models, and we demonstrate that dark matter annihilation scenarios can predict index values that require "extreme" parameters for background-only explanations.Comment: v1: 11 pages, 7 figures, 1 table, revtex4; v2: 13 pages, 8 figures, 1 table, revtex4, Figure 4 added, minor additions made to text, references added, conclusions unchanged, published versio

Constraints on dark matter models from a Fermi LAT search for high-energy cosmic-ray electrons from the Sun

During its first year of data taking, the Large Area Telescope (LAT) onboard the Fermi Gamma-Ray Space Telescope has collected a large sample of high-energy cosmic-ray electrons and positrons (CREs). We present the results of a directional analysis of the CRE events, in which we searched for a flux excess correlated with the direction of the Sun. Two different and complementary analysis approaches were implemented, and neither yielded evidence of a significant CRE flux excess from the Sun. We derive upper limits on the CRE flux from the Sun's direction, and use these bounds to constrain two classes of dark matter models which predict a solar CRE flux: (1) models in which dark matter annihilates to CREs via a light intermediate state, and (2) inelastic dark matter models in which dark matter annihilates to CREs.Comment: 18 pages, 8 figures, accepted for publication in Physical Review D - contact authors: Francesco Loparco ([email protected]), M. Nicola Mazziotta ([email protected]) and Jennifer Siegal-Gaskins ([email protected]

A luminosity constraint on the origin of unidentified high energy sources

The identification of point sources poses a great challenge for the high energy community. We present a new approach to evaluate the likelihood of a set of sources being a Galactic population based on the simple assumption that galaxies similar to the Milky Way host comparable populations of gamma-ray emitters. We propose a luminosity constraint on Galactic source populations which complements existing approaches by constraining the abundance and spatial distribution of any objects of Galactic origin, rather than focusing on the properties of a specific candidate emitter. We use M31 as a proxy for the Milky Way, and demonstrate this technique by applying it to the unidentified EGRET sources. We find that it is highly improbable that the majority of the unidentified EGRET sources are members of a Galactic halo population (e.g., dark matter subhalos), but that current observations do not provide any constraints on all of these sources being Galactic objects if they reside entirely in the disk and bulge. Applying this method to upcoming observations by the Fermi Gamma-ray Space Telescope has the potential to exclude association of an even larger number of unidentified sources with any Galactic source class.Comment: 18 pages, 4 figures, to appear in JPhys

Evolution of Robustness to Noise and Mutation in Gene Expression Dynamics

Phenotype of biological systems needs to be robust against mutation in order to sustain themselves between generations. On the other hand, phenotype of an individual also needs to be robust against fluctuations of both internal and external origins that are encountered during growth and development. Is there a relationship between these two types of robustness, one during a single generation and the other during evolution? Could stochasticity in gene expression have any relevance to the evolution of these robustness? Robustness can be defined by the sharpness of the distribution of phenotype; the variance of phenotype distribution due to genetic variation gives a measure of `genetic robustness' while that of isogenic individuals gives a measure of `developmental robustness'. Through simulations of a simple stochastic gene expression network that undergoes mutation and selection, we show that in order for the network to acquire both types of robustness, the phenotypic variance induced by mutations must be smaller than that observed in an isogenic population. As the latter originates from noise in gene expression, this signifies that the genetic robustness evolves only when the noise strength in gene expression is larger than some threshold. In such a case, the two variances decrease throughout the evolutionary time course, indicating increase in robustness. The results reveal how noise that cells encounter during growth and development shapes networks' robustness to stochasticity in gene expression, which in turn shapes networks' robustness to mutation. The condition for evolution of robustness as well as relationship between genetic and developmental robustness is derived through the variance of phenotypic fluctuations, which are measurable experimentally.Comment: 25 page