A competitive assessment of the renewable energy equipment industry /

Item 231-B-1

Illinois solar weather program /

"March 1983."

Interrogation of Gender Identity: Aesthetic Consumption of Korean Television Dramas by Young Women in China

Given the popularity of Korean television dramas among various age groups in other countries, one would expect to see a similar pattern of consumption across different ages in China. Instead, we see high levels of consumption of Korean dramas by a very specific demographic. Why do young Chinese females consume Korean dramas at such high levels? I argue that young Chinese women’s heavy consumption of Korean dramas that portray a particular aesthetic of self and familial resolution may be explained by a need to redress contemporary psychological issues related to gendered self-identity. I posit that the identity formation processes of this particular demographic has been shaped by changes in family dynamics that stem from social and political restructuring in the 1980s, particularly the one-child policy. Thus, this thesis explores how the consumption of Korean dramas by young females in China may be understood as an implicit interrogation of gendered identity.

Spider ballooning in soybean and non-crop areas of southeast Queensland

Ballooning is a form of aerial movement practiced by most miniature and some adult spiders. Very few studies have investigated the composition and rate of spider ballooning in Australian agroecosystems. Water traps were used to compare ballooning rates in irrigated soybean crops and nearby non-crop areas in southeast Queensland over two summer seasons. The highest ballooning rate (14.8 spiders/m(2) per day) was recorded in a soybean field, non-crop areas (7.0 spiders/m(2) per day) and a dry land mungbean field (6.8 spiders/m(2) per day) having similar rates. Spider ballooning in soybean increased throughout the season and showed three peaks and intervening troughs. A similar pattern in ballooning peaks was observed in non-crop areas however the numbers were lower. Peaks in ballooning activity where synchronised across habitat types and some spider groups. Composition of the ballooning fauna was different from that of the ground-dwelling fauna, some families being present in both. Ballooning is an important behaviour in terms of population dynamics for a number of spider groups in soybean and the implications for pest control are discussed. (C) 2004 Elsevier BN. All rights reserved.

Defining nicotine dependence for genetic research: evidence from Australian twins

Background. Whether current criteria used to define nicotine dependence are informative for genetic research is an important empirical question. The authors used items of the DSM-IV and of the Heaviness of Smoking Index to characterize the nicotine dependence phenotype and to identify salient symptoms in a genetically informative community sample of Australian young adult female and mate twins. Method. Phenotypic and genetic factor analyses were performed on nine dependence symptoms (the seven DSM-IV substance dependence criteria and the two Heaviness of Smoking Index (HSI) items derived from the Fagerstrom Tolerance Questionnaire, time to first cigarette in the morning and number of cigarettes smoked per day). Phenotypic and genetic analyses were restricted to ever smokers. Results. Phenotypic nicotine dependence symptom covariation was best captured by two factors with a similar pattern of factor loadings for women and men. In genetic factor analysis item covariation was best captured by two genetic but one shared environmental factor for both women and men; however, item factor loadings differed by gender. All nicotine dependence symptoms were substantially heritable, except for the DSM-IV criterion of 'giving up or reducing important activities in order to smoke', which was weakly familial. Conclusions. The salient behavioral indices of nicotine dependence are similar for women and men. DSM-IV criteria of tolerance, withdrawal, and experiencing difficulty quitting and HSI items time to first cigarette in the morning and number of cigarettes smoked per day may represent the most highly heritable symptoms of nicotine dependence for both women and men.

The influence of dopamine on semantic activation in Parkinson's disease: Evidence from a multipriming task

Research has suggested that semantic processing deficits in Parkinson's disease (PD) are related to striatal dopamine deficiency. As an investigation of the influence of dopamine on semantic activation in PD, 7 participants with PD performed a lexical-decision task when on and off levodopa medication. Seven healthy controls matched to the participants with PD in terms of sex, age, and education also participated in the study. By use of a multipriming paradigm, whereby 2 prime words were presented prior to the target word, semantic priming effects were measured across stimulus onset asynchronies (SOAs) of 250 Ins and 1,200 Ins. The results revealed a similar pattern of priming across SOAs for the control group and the PD participants on medication. In contrast, within-group comparisons revealed that automatic semantic activation was compromised in PD participants when off medication. The implications of these results for the neuromodulatory influence of dopamine on semantic processing in PD are discussed.

Computing with infinite networks

For neural networks with a wide class of weight-priors, it can be shown that in the limit of an infinite number of hidden units the prior over functions tends to a Gaussian process. In this paper analytic forms are derived for the covariance function of the Gaussian processes corresponding to networks with sigmoidal and Gaussian hidden units. This allows predictions to be made efficiently using networks with an infinite number of hidden units, and shows that, somewhat paradoxically, it may be easier to compute with infinite networks than finite ones.

Computation with infinite neural networks

For neural networks with a wide class of weight priors, it can be shown that in the limit of an infinite number of hidden units, the prior over functions tends to a gaussian process. In this article, analytic forms are derived for the covariance function of the gaussian processes corresponding to networks with sigmoidal and gaussian hidden units. This allows predictions to be made efficiently using networks with an infinite number of hidden units and shows, somewhat paradoxically, that it may be easier to carry out Bayesian prediction with infinite networks rather than finite ones.

Point-wise confidence interval estimation by neural networks: A comparative study based on automotive engine calibration.

In developing neural network techniques for real world applications it is still very rare to see estimates of confidence placed on the neural network predictions. This is a major deficiency, especially in safety-critical systems. In this paper we explore three distinct methods of producing point-wise confidence intervals using neural networks. We compare and contrast Bayesian, Gaussian Process and Predictive error bars evaluated on real data. The problem domain is concerned with the calibration of a real automotive engine management system for both air-fuel ratio determination and on-line ignition timing. This problem requires real-time control and is a good candidate for exploring the use of confidence predictions due to its safety-critical nature.

A variational approach to learning curves

We combine the replica approach from statistical physics with a variational approach to analyze learning curves analytically. We apply the method to Gaussian process regression. As a main result we derive approximative relations between empirical error measures, the generalization error and the posterior variance.

Designing a support system for aerospace maintenance supply chains

Purpose - To develop a systems strategy for supply chain management in aerospace maintenance, repair and overhaul (MRO). Design/methodology/approach - A standard systems development methodology has been followed to produce a process model (i.e. the AMSCR model); an information model (i.e. business rules) and a computerised information management capability (i.e. automated optimisation). Findings - The proof of concept for this web-based MRO supply chain system has been established through collaboration with a sample of the different types of supply chain members. The proven benefits comprise new potential to minimise the stock holding costs of the whole supply chain whilst also minimising non-flying time of the aircraft that the supply chain supports. Research limitations/implications - The scale of change needed to successfully model and automate the supply chain is vast. This research is a limited-scale experiment intended to show the power of process analysis and automation, coupled with strategic use of management science techniques, to derive tangible business benefit. Practical implications - This type of system is now vital in an industry that has continuously decreasing profit margins; which in turn means pressure to reduce servicing times and increase the mean time between them. Originality/value - Original work has been conducted at several levels: process, information and automation. The proof-of-concept system has been applied to an aircraft MRO supply chain. This is an area of research that has been neglected, and as a result is not well served by current systems solutions. © Emerald Group Publishing Limited.

Measuring the Big Five with single items using a bipolar response scale

The convergence on the Big Five in personality theory has produced a demand for efficient yet psychometrically sound measures. Therefore, five single-item measures, using bipolar response scales, were constructed to measure the Big Five and evaluated in terms of their convergent and off-diagonal divergent properties, their pattern of criterion correlations and their reliability when compared with four longer Big Five measures. In a combined sample (N?=?791) the Single-Item Measures of Personality (SIMP) demonstrated a mean convergence of r?=?0.61 with the longer scales. The SIMP also demonstrated acceptable reliability, self–other accuracy, and divergent correlations, and a closely similar pattern of criterion correlations when compared with the longer scales. It is concluded that the SIMP offer a reasonable alternative to longer scales, balancing the demands of brevity versus reliability and validity.

Emulation of random output simulators

Computer models, or simulators, are widely used in a range of scientific fields to aid understanding of the processes involved and make predictions. Such simulators are often computationally demanding and are thus not amenable to statistical analysis. Emulators provide a statistical approximation, or surrogate, for the simulators accounting for the additional approximation uncertainty. This thesis develops a novel sequential screening method to reduce the set of simulator variables considered during emulation. This screening method is shown to require fewer simulator evaluations than existing approaches. Utilising the lower dimensional active variable set simplifies subsequent emulation analysis. For random output, or stochastic, simulators the output dispersion, and thus variance, is typically a function of the inputs. This work extends the emulator framework to account for such heteroscedasticity by constructing two new heteroscedastic Gaussian process representations and proposes an experimental design technique to optimally learn the model parameters. The design criterion is an extension of Fisher information to heteroscedastic variance models. Replicated observations are efficiently handled in both the design and model inference stages. Through a series of simulation experiments on both synthetic and real world simulators, the emulators inferred on optimal designs with replicated observations are shown to outperform equivalent models inferred on space-filling replicate-free designs in terms of both model parameter uncertainty and predictive variance.

A basis function approach to Bayesian inference in diffusion processes

In this paper, we present a framework for Bayesian inference in continuous-time diffusion processes. The new method is directly related to the recently proposed variational Gaussian Process approximation (VGPA) approach to Bayesian smoothing of partially observed diffusions. By adopting a basis function expansion (BF-VGPA), both the time-dependent control parameters of the approximate GP process and its moment equations are projected onto a lower-dimensional subspace. This allows us both to reduce the computational complexity and to eliminate the time discretisation used in the previous algorithm. The new algorithm is tested on an Ornstein-Uhlenbeck process. Our preliminary results show that BF-VGPA algorithm provides a reasonably accurate state estimation using a small number of basis functions.

A comparison of variational and Markov chain Monte Carlo methods for inference in partially observed stochastic dynamic systems

In recent work we have developed a novel variational inference method for partially observed systems governed by stochastic differential equations. In this paper we provide a comparison of the Variational Gaussian Process Smoother with an exact solution computed using a Hybrid Monte Carlo approach to path sampling, applied to a stochastic double well potential model. It is demonstrated that the variational smoother provides us a very accurate estimate of mean path while conditional variance is slightly underestimated. We conclude with some remarks as to the advantages and disadvantages of the variational smoother. © 2008 Springer Science + Business Media LLC.