Bridiging designs for conjoint analysis: The issue of attribute importance.

Abstract: Conjoint analysis studies involving many attributes and attribute levels often occur in practice. Because such studies can cause respondent fatigue and lack of cooperation, it is important to design data collection tasks that reduce those problems. Bridging designs, incorporating two or more task subsets with overlapping attributes, can presumably lower task difficulty in such cases. In this paper, we present results of a study examining the effects on predictive validity of bridging design decisions involving important or unimportant attributes as links (bridges) between card-sort tasks and the degree of balance and consistency in estimated attribute importance across tasks. We also propose a new symmetric procedure, Symbridge, to scale the bridged conjoint solutions.Studies; Cooperation; Data; Problems; Effects; Decisions;

Learning about a Moving Target in Resource Management: Optimal Bayesian Disease Control

Resource managers must often make difficult choices in the face of imperfectly observed and dynamically changing systems (e.g., livestock, fisheries, water, and invasive species). A rich set of techniques exists for identifying optimal choices when that uncertainty is assumed to be understood and irreducible. Standard optimization approaches, however, cannot address situations in which reducible uncertainty applies to either system behavior or environmental states. The adaptive management literature overcomes this limitation with tools for optimal learning, but has been limited to highly simplified models with state and action spaces that are discrete and small. We overcome this problem by using a recently developed extension of the Partially Observable Markov Decision Process (POMDP) framework to allow for learning about a continuous state. We illustrate this methodology by exploring optimal control of bovine tuberculosis in New Zealand cattle. Disease testing—the control variable—serves to identify herds for treatment and provides information on prevalence, which is both imperfectly observed and subject to change due to controllable and uncontrollable factors. We find substantial efficiency losses from both ignoring learning (standard stochastic optimization) and from simplifying system dynamics (to facilitate a typical, simple learning model), though the latter effect dominates in our setting. We also find that under an adaptive management approach, simplifying dynamics can lead to a belief trap in which information gathering ceases, beliefs become increasingly inaccurate, and losses abound

Grey and white matter differences in Chronic Fatigue Syndrome : A voxel-based morphometry study

Conflicts of interest and source of funding The authors declare no conflicts of interest. This research was funded by the Medical Research Council (MR/J002712/1). AF is supported by Research Capability Funding from the Newcastle upon Tyne Hospitals NHS Foundation Trust and the Northumberland, Tyne and Wear NHS Foundation Trust.Peer reviewedPublisher PD

The evolution of electron overdensities in magnetic fields

When a neutral gas impinges on a stationary magnetized plasma an enhancement in the ionization rate occurs when the neutrals exceed a threshold velocity. This is commonly known as the critical ionization velocity effect. This process has two distinct timescales: an ion–neutral collision time and electron acceleration time. We investigate the energization of an ensemble of electrons by their self-electric field in an applied magnetic field. The evolution of the electrons is simulated under different magnetic field and density conditions. It is found that electrons can be accelerated to speeds capable of electron impact ionization for certain conditions. In the magnetically dominated case the energy distribution of the excited electrons shows that typically 1% of the electron population can exceed the initial electrostatic potential associated with the unbalanced ensemble of electrons

The Hurst Exponent of Fermi GRBs

Using a wavelet decomposition technique, we have extracted the Hurst exponent for a sample of 46 long and 22 short Gamma-ray bursts (GRBs) detected by the Gamma-ray Burst Monitor (GBM) aboard the Fermi satellite. This exponent is a scaling parameter that provides a measure of long-range behavior in a time series. The mean Hurst exponent for the short GRBs is significantly smaller than that for the long GRBs. The separation may serve as an unbiased criterion for distinguishing short and long GRBs.Comment: Accepted for publication in Monthly Notices of the Royal Astronomical Societ

Time-Resolved Infrared Radiometric Imaging of Coatings

Thermal techniques have matured for the nondestructive characterization of the internal structure of opaque solids in recent years. While CW-modulated thermal wave imaging techniques have proven applicable to the inspection of many types of structures, difficulties arise when the layers are thick or have low thermal diffusivity. The depth, ℓ, into the specimen which can be probed is approximately one thermal diffusion length, δ = (2α/ω)l/2 where α is the thermal diffusivity and ω is the angular modulation frequency. When ℓ/δ is large because of a low thermal diffusivity, the modulation frequency must be lowered to allow the full thickness of the structure to be examined. As the modulation frequency is decreased, the dwell time required at each point for construction of an image by a point-scanning technique increases as do the data acquisition times. For low diffusivity materials, the data acquisition times are too long for thermal wave imaging to be a feasible routine inspection technique