Proton Spectrum at the Jupiter Laser Facility of LLNL

This paper looks at tungsten samples irradiated by beams of protons, gammas, electrons and positrons at the Jupiter Laser Facility of Lawrence Livermore National Laboratory (LLNL). The resulting unstable nuclei created are identified using their gamma spectra. These spectra were taken, usually within an hour of irradiation, for periods up to 48 hrs. In several cases there are two isotopes, one of Rhenium and the other of Tantalum, that emit the same gamma lines. These pairs often involve a long-lived and a short-lived candidate. Spectra were taken 80 days after initial exposure and the long-lived candidates are ruled out

Examining Uncertainty and Misspecification of Attributes in Cognitive Diagnostic Models

In recent years, cognitive diagnostic models (CDMs) have been widely used in educational assessment to provide a diagnostic profile (mastery/non-mastery) analysis for examinees, which gives insights into learning and teaching. However, there is often uncertainty about the specification of the Q-matrix that is required for CDMs, given that it is based on expert judgment. The current study uses a Bayesian approach to examine recovery of Q-matrix elements in the presence of uncertainty about some elements. The first simulation examined the situation where there is complete uncertainty about whether or not an attribute is required, when in fact it is required. The simulation results showed that recovery was generally excellent. However, recovery broke down when other elements of the Q-matrix were misspecified. Further simulations showed that, if one has some information about the attributes for a few items, then recovery improves considerably, but this also depends on how many other elements are misspecified. A second set of simulations examined the situation where uncertain Q-matrix elements were scattered throughout the Q-matrix. Recovery was generally excellent, even when some other elements were misspecified. A third set of simulations showed that using more informative priors did not uniformly improve recovery. An application of the approach to data from TIMSS (2007) suggested some alternative Q-matrices

Model risk in real option valuation

We introduce a general decision-tree framework to value an option to invest/divest in a project, focusing on the model risk inherent in the assumptions made by standard real option valuation methods. We examine how real option values depend on the dynamics of project value and investment costs, the frequency of exercise opportunities, the size of the project relative to initial wealth, the investor’s risk tolerance (and how it changes with wealth) and several other choices about model structure. For instance, contrary to stylised facts from previous literature, real option values can actually decrease with the volatility of the underlying project value and increase with investment costs. And large projects can be more or less attractive than small projects (ceteris paribus) depending on the risk tolerance of the investor, how this changes with wealth, and the structure of costs to invest in the project

An examination of new product diffusion in Japan and Taiwan : a thesis presented in partial fulfilment of the requirements of the degree of Master of Business Studies (Hons) at Massey University

The diffusion of new products and services is an important marketing issue given the vast number of new products, brands, and brand extensions being developed and launched every year. Shorter product life cycles mean companies have less time to recoup development costs and optimise elements of the marketing mix. Accordingly, any prior information about the particular innovation or market is essential in aiding decision making. As important is the development of models that can forecast sales and diffusion patterns prior to product launch and during the early stage of the product's life. Furthermore, understanding the diffusion dynamics of different geographic regions is a prerequisite for success in an increasingly global environment that retains many cultural nuances. All of these issues are addressed to some extent in this thesis, but it is the last of these which is the main focus. The Bass diffusion model of new product growth (Bass, 1969) is a mathematical model which focuses on the process by which an innovation is adopted within a social system over time. The original model has three parameters: external influence, p, which represents the impact of factors external to the adopting population such as mass media and advertising; internal influence, q, which includes both verbal and nonverbal interpersonal effects within the adopting population; and the expected total number of adopters or market potential, m. Being inherently non-linear, the model is able to duplicate the s-shaped cumulative adoption curve regularly observed for new products (Dodds, 1973; Sharif and Ramanathan, 1981; Mahajan, Muller and Bass, 1995)

Nanoscale field effect transistor for biomolecular signal amplification

We report amplification of biomolecular recognition signal in lithographically defined silicon nanochannel devices. The devices are configured as field effect transistors (FET) in the reversed source-drain bias region. The measurement of the differential conductance of the nanowire channels in the FET allows sensitive detection of changes in the surface potential due to biomolecular binding. Narrower silicon channels demonstrate higher sensitivity to binding due to increased surface-to-volume ratio. The operation of the device in the negative source-drain region demonstrates signal amplification. The equivalence between protein binding and change in the surface potential is described