Computational studies of the transverse structure of AGN jets

Both the emission properties and the evolution of the radio jets of Active Galactic Nuclei are dependent on the magnetic (B) fields that thread them. A number of observations of AGN jets suggest that the B fields they carry have a significant helical component, at least on parsec scales. This thesis uses a model, first proposed by Laing and then developed by Papageorgiou, to explore how well the observed properties of AGN jets can be reproduced by assuming a helical B field with three parameters; pitch angle, viewing angle and degree of entanglement. This model has been applied to multifrequency Very Long Baseline Interferometry (VLBI) observations of the AGN jets of Markarian 501 and M87, making it possible to derive values for the helical pitch angle, the viewing angle and the degree of entanglement for these jets. Faraday rotation measurements are another important tool for investigating the B fields of AGN jets. A helical B field component should result in a systematic gradient in the observed Faraday rotation across the jet. Real observed radio images have finite resolution; typical beam sizes for cm-wavelength VLBI observations are often comparable to or larger than the intrinsic jet widths, raising questions about how well resolved a jet must be in the transverse direction in order to reliably detect transverse Faraday-rotation structure. This thesis presents results of Monte Carlo simulations of Faraday rotation images designed to directly investigate this question, together with a detailed investigation into the probabilities of observing spurious Faraday Rotation gradients as a result of random noise and finite resolution. These simulations clearly demonstrate the possibility of detecting transverse Faraday-rotation structures even when the intrinsic jet widths are appreciably smaller than the beam width.

Missing data in randomized clinical trials for weight loss: scope of the problem, state of the field, and performance of statistical methods.

BACKGROUND: Dropouts and missing data are nearly-ubiquitous in obesity randomized controlled trails, threatening validity and generalizability of conclusions. Herein, we meta-analytically evaluate the extent of missing data, the frequency with which various analytic methods are employed to accommodate dropouts, and the performance of multiple statistical methods. METHODOLOGY/PRINCIPAL FINDINGS: We searched PubMed and Cochrane databases (2000-2006) for articles published in English and manually searched bibliographic references. Articles of pharmaceutical randomized controlled trials with weight loss or weight gain prevention as major endpoints were included. Two authors independently reviewed each publication for inclusion. 121 articles met the inclusion criteria. Two authors independently extracted treatment, sample size, drop-out rates, study duration, and statistical method used to handle missing data from all articles and resolved disagreements by consensus. In the meta-analysis, drop-out rates were substantial with the survival (non-dropout) rates being approximated by an exponential decay curve (e(-lambdat)) where lambda was estimated to be .0088 (95% bootstrap confidence interval: .0076 to .0100) and t represents time in weeks. The estimated drop-out rate at 1 year was 37%. Most studies used last observation carried forward as the primary analytic method to handle missing data. We also obtained 12 raw obesity randomized controlled trial datasets for empirical analyses. Analyses of raw randomized controlled trial data suggested that both mixed models and multiple imputation performed well, but that multiple imputation may be more robust when missing data are extensive. CONCLUSION/SIGNIFICANCE: Our analysis offers an equation for predictions of dropout rates useful for future study planning. Our raw data analyses suggests that multiple imputation is better than other methods for handling missing data in obesity randomized controlled trials, followed closely by mixed models. We suggest these methods supplant last observation carried forward as the primary method of analysis.

Bunching-induced optical nonlinearity and instability in cold atoms [Invited].

We report a new nonlinear optical process that occurs in a cloud of cold atoms at low-light-levels when the incident optical fields simultaneously polarize, cool, and spatially-organize the atoms. We observe an extremely large effective fifth-order nonlinear susceptibility of χ(⁵) = 7.6 × 10⁻¹⁵ (m/V)⁴, which results in efficient Bragg scattering via six-wave mixing, slow group velocities (∼ c/10⁵), and enhanced atomic coherence times (> 100 μs). In addition, this process is particularly sensitive to the atomic temperatures, and provides a new tool for in-situ monitoring of the atomic momentum distribution in an optical lattice. For sufficiently large light-matter couplings, we observe an optical instability for intensities as low as ∼ 1 mW/cm² in which new, intense beams of light are generated and result in the formation of controllable transverse optical patterns.

Parliamentary party loyalty and party family: the missing link?

info:eu-repo/semantics/inPress

Simulation of transverse and longitudinal magnetic ripple structures induced by surface anisotropy

Micromagnetic ripple structures on the surfaces of thick specimens of ultra-soft magnetic material having strong surface anisotropy Ks favouring out-of-surface magnetization have been calculated. These ripples have wavelengths of the order of 0.1 μm and extend to a depth ∼ √A/Ms, where A is the exchange constant and Ms is the saturation magnetization. The wave-vectors of the ripple structures are either transverse or parallel to the bulk magnetization. Both structures have lower energy than the one-dimensional structure discussed by O'Handley and Woods, and they exhibit stronger normal magnetization. The transverse structure requires a surface anisotropy Ks ≥ 0.80K0, where is that required for the one-dimensional structure. The threshold for longitudinal ripples is 0.84K0. It is suggested that the transverse structure probably constitutes the ground state. The magnitudes of Ks and A should be obtainable from measurements of the ripple wavelength and amplitude, and Ms.

Towards the sustainable use of Europe’s forests: a centre for European forest science! – Some missing catalytic elements?

The Symposium, “Towards the sustainable use of Europe’s forests”, with sub-title “Forest ecosystem and landscape research: scientific challenges and opportunities” lists three fundamental substantive areas of research that are involved: Forest management and practices, Ecosystem processes and functional ecology, and Environmental economics and sociology. This paper argues that there are essential catalytic elements missing! Without these elements there is great danger that the aimed-for world leadership in the forest sciences will not materialize. What are the missing elements? All the sciences, and in particular biology, environmental sciences, sociology, economics, and forestry have evolved so that they include good scientific methodology. Good methodology is imperative in both the design and analysis of research studies, the management of research data, and in the interpretation of research finding. The methodological disciplines of Statistics, Modelling and Informatics (“SMI”) are crucial elements in a proposed Centre of European Forest Science, and the full involvement of professionals in these methodological disciplines is needed if the research of the Centre is to be world-class. Distributed Virtual Institute (DVI) for Statistics, Modelling and Informatics in Forestry and the Environment (SMIFE) is a consortium with the aim of providing world-class methodological support and collaboration to European research in the areas of Forestry and the Environment. It is suggested that DVI: SMIFE should be a formal partner in the proposed Centre for European Forest Science.

The missing link between information and action: hastenings and delays as universal reactions to performance feedback

This chapter focuses on what the key decision makers in organizations decide after having received information on the current state of the organizational performance. Because of strong attributions to success and failure, it is impossible to predict in advance which concrete actions will occur. We can however find out what kinds of actions are decided upon by means of an organizational learning model that focuses on the hastenings and delays after performance feedback. As an illustration, the responses to performance signals by trainers and club owners in Dutch soccer clubs are analyzed.