Windtunnel model position and orientation

In this contribution the determination of the position of moving and deforming objects in windtunnels from CCD camera information is studied. An analytical approach is discussed which solves the problem directly from manipulating nonlinear distance formulae. Also a least-squares approach is given, which is most convenient to implement from a numerical point of view

Optimizing the Majorana character of SQUIDs with topologically non-trivial barriers

We have modeled SQUIDs with topologically non-trivial superconducting junctions and performed an optimization study on the Majorana fermion detection. We find that the SQUID parameters beta_L, and beta_C can be used to increase the ratio of Majorana tunneling to standard Cooper pair tunneling by more than two orders of magnitude. Most importantly, we show that dc SQUIDs including topologically trivial components can still host strong signatures of the Majorana fermion. This paves the way towards the experimental verification of the theoretically predicted Majorana fermion.Comment: accepted by Physical Review

Examining the Dynamic Structure of Daily Internalizing and Externalizing Behavior at Multiple Levels of Analysis

Psychiatric diagnostic covariation suggests that the underlying structure of psychopathology is not one of circumscribed disorders. Quantitative modeling of individual differences in diagnostic patterns has uncovered several broad domains of mental disorder liability, of which the Internalizing and Externalizing spectra have garnered the greatest support. These dimensions have generally been estimated from lifetime or past-year comorbidity patters, which are distal from the covariation of symptoms and maladaptive behavior that ebb and flow in daily life. In this study, structural models are applied to daily diary data (Median = 94 days) of maladaptive behaviors collected from a sample (N = 101) of individuals diagnosed with personality disorders. Using multilevel and unified structural equation modeling, between-person, within-person, and person-specific structures were estimated from 16 behaviors that are encompassed by the Internalizing and Externalizing spectra. At the between-person level (i.e., individual differences in average endorsement across days) we found support for a two-factor Internalizing-Externalizing model, which exhibits significant associations with corresponding diagnostic spectra. At the within-person level (i.e., dynamic covariation among daily behavior pooled across individuals) we found support for a more differentiated, four-factor, Negative Affect-Detachment-Hostility-Impulsivity structure. Finally, we demonstrate that the person-specific structures of associations between these four domains are highly idiosyncratic

Examining the Dynamic Structure of Daily Internalizing and Externalizing Behavior at Multiple Levels of Analysis

Psychiatric diagnostic covariation suggests that the underlying structure of psychopathology is not one of circumscribed disorders. Quantitative modeling of individual differences in diagnostic patterns has uncovered several broad domains of mental disorder liability, of which the Internalizing and Externalizing spectra have garnered the greatest support. These dimensions have generally been estimated from lifetime or past-year comorbidity patters, which are distal from the covariation of symptoms and maladaptive behavior that ebb and flow in daily life. In this study, structural models are applied to daily diary data (Median = 94 days) of maladaptive behaviors collected from a sample (N = 101) of individuals diagnosed with personality disorders. Using multilevel and unified structural equation modeling, between-person, within-person, and person-specific structures were estimated from 16 behaviors that are encompassed by the Internalizing and Externalizing spectra. At the between-person level (i.e., individual differences in average endorsement across days) we found support for a two-factor Internalizing-Externalizing model, which exhibits significant associations with corresponding diagnostic spectra. At the within-person level (i.e., dynamic covariation among daily behavior pooled across individuals) we found support for a more differentiated, four-factor, Negative Affect-Detachment-Hostility-Impulsivity structure. Finally, we demonstrate that the person-specific structures of associations between these four domains are highly idiosyncratic

Person-Specific Non-shared Environmental Influences in Intra-individual Variability : A Preliminary Case of Daily School Feelings in Monozygotic Twins

Most behavioural genetic studies focus on genetic and environmental influences on inter-individual phenotypic differences at the population level. The growing collection of intensive longitudinal data in social and behavioural science offers a unique opportunity to examine genetic and environmental influences on intra-individual phenotypic variability at the individual level. The current study introduces a novel idiographic approach and one novel method to investigate genetic and environmental influences on intra-individual variability by a simple empirical demonstration. Person-specific non-shared environmental influences on intra-individual variability of daily school feelings were estimated using time series data from twenty-one pairs of monozygotic twins (age = 10 years, 16 female pairs) over two consecutive weeks. Results showed substantial inter-individual heterogeneity in person-specific non-shared environmental influences. The current study represents a first step in investigating environmental influences on intra-individual variability with an idiographic approach, and provides implications for future behavioural genetic studies to examine developmental processes from a microscopic angle

Genomic profiling by DNA amplification of laser capture microdissected tissues and array CGH.

Comparative genomic hybridization by means of BAC microarrays (array CGH) allows high-resolution profiling of copy-number aberrations in tumor DNA. However, specific genetic lesions associated with small but clinically relevant tumor areas may pass undetected due to intra-tumor heterogeneity and/or the presence of contaminating normal cells. Here, we show that the combination of laser capture microdissection, phi29 DNA polymerase-mediated isothermal genomic DNA amplification, and array CGH allows genomic profiling of very limited numbers of cells. Moreover, by means of simple statistical models, we were able to bypass the exclusion of amplification distortions and variability prone areas, and to detect tumor-specific chromosomal gains and losses. We applied this new combined experimental and analytical approach to the genomic profiling of colorectal adenomatous polyps and demonstrated our ability to accurately detect single copy gains and losses affecting either whole chromosomes or small genomic regions from as little as 2 ng of DNA or 1000 microdissected cells

Disease surveillance and risk factors affecting mortality of captive cirl buntings (Emberiza cirlus) in a translocation for conservation purposes

Cirl buntings in the UK were translocated over a 5-year period by collecting chicks from the residual population, hand-rearing and releasing them at a site in Cornwall with the aim of establishing a second breeding population. Because mortality and morbidity during captivity restrict the number and fitness of individuals available for release, selected parasites were monitored in the captive chicks, and all deaths were investigated by autopsy, histopathology and bacteriology. Risk factors associated with captive deaths were analysed. Annual mortality during captivity ranged from 4% (3 of 75 chicks in 2006) to 42% (26 of 73 in 2007) of chicks collected. Infectious disease associated with immunosuppression was an important factor in many deaths, and chicks collected with lower body weight were at greater risk of mortality. These findings emphasise the need for rigorous monitoring of all aspects of captive care during passerine translocations and provide evidence-based recommendations for future projects

PySE: Software for Extracting Sources from Radio Images

PySE is a Python software package for finding and measuring sources in radio telescope images. The software was designed to detect sources in the LOFAR telescope images, but can be used with images from other radio telescopes as well. We introduce the LOFAR Telescope, the context within which PySE was developed, the design of PySE, and describe how it is used. Detailed experiments on the validation and testing of PySE are then presented, along with results of performance testing. We discuss some of the current issues with the algorithms implemented in PySE and their inter- action with LOFAR images, concluding with the current status of PySE and its future development.Comment: 26 pages, 6 figure

In silico evolution of diauxic growth

The glucose effect is a well known phenomenon whereby cells, when presented with two different nutrients, show a diauxic growth pattern, i.e. an episode of exponential growth followed by a lag phase of reduced growth followed by a second phase of exponential growth. Diauxic growth is usually thought of as a an adaptation to maximise biomass production in an environment offering two or more carbon sources. While diauxic growth has been studied widely both experimentally and theoretically, the hypothesis that diauxic growth is a strategy to increase overall growth has remained an unconfirmed conjecture. Here, we present a minimal mathematical model of a bacterial nutrient uptake system and metabolism. We subject this model to artificial evolution to test under which conditions diauxic growth evolves. As a result, we find that, indeed, sequential uptake of nutrients emerges if there is competition for nutrients and the metabolism/uptake system is capacity limited. However, we also find that diauxic growth is a secondary effect of this system and that the speed-up of nutrient uptake is a much larger effect. Notably, this speed-up of nutrient uptake coincides with an overall reduction of efficiency. Our two main conclusions are: (i) Cells competing for the same nutrients evolve rapid but inefficient growth dynamics. (ii) In the deterministic models we use here no substantial lag-phase evolves. This suggests that the lag-phase is a consequence of stochastic gene expression

LISREL analysis of twin data with structured means

Introduces a method to test the hypothesis that the phenotypic means and the phenotypic covariances can be modeled with the same common genetic and environmental factors. LISREL can be used to implement the method. An illustration with simulated twin data is provided