Habitat requirements of the yellow-footed antechinus (Antechinus flavipes) in box–ironbark forest, Victoria, Australia

Understanding the habitat requirements of a species is critical for effective conservation-based management. In this study, we investigated the influence of forest structure on the distribution of the yellow-footed antechinus (Antechinus flavipes), a small dasyurid marsupial characteristic of dry forests on the inland side of the Great Dividing Range, Australia. Hair-sampling tubes were used to determine the occurrence of A. flavipes at 60 sites stratified across one of the largest remaining tracts of dry box–ironbark forest in south-eastern Australia. We considered the role of six potential explanatory variables: large trees, hollow-bearing trees, coppice hollows, logs, rock cover and litter. Logistic regression models were examined using an information-theoretic approach to determine the variables that best explained the presence or absence of the species. Hierarchical partitioning was employed to further explore relationships between occurrence of A. flavipes and explanatory variables. Forest structure accounted for a substantial proportion of the variation in occurrence of A. flavipes between sites. The strongest influence on the presence of A. flavipes was the cover of litter at survey sites. The density of hollow-bearing trees and rock cover were also positive influences. The conservation of A. flavipes will be enhanced by retention of habitat components that ensure a structurally complex environment in box–ironbark forests. This will also benefit the conservation of several threatened species in this dry forest ecosystem.

So flat, so cute! Robots, superflatness and asian architectural futures

Many depictions of urban futures have a distinctly Asian flavour. There have been numerous visions of highly technological futures whose environments extrapolate present societies into futures technically, culturally and politically dominated by China or Japan, Such futures are portrayed as both exciting and threatening, to the point that the Japanese academic and cultural critic Toshiya Ueno used the term ‘Techno-Orientalism’ to describe the phenomenon. Nevertheless, whether Western interest is Orientalist or not, Asian architects are also increasingly looking to their own contemporary and future cultures for inspiration. This paper will discuss two manifestations of this. The first is Thai architect Sumet Jumsai’s Bank of Asia. Unlike contemporaneous English hightech buildings, with their coldly mechanistic representation of ducts and struts, Jumsai’s Bank of Asia, takes on the anthropomorphic character of Japanese scifi robots. It is endearing, friendly, even cute. The second example is what might be termed superflat architecture, from the term coined by the artist Takashi Murakami to describe an aesthetic of intrinsic flatness, eliminating depth in favour of skin and surface. The emergence of Techno-Cute and Superflat architecture suggest contemporary Asian architectural sensibilities that neither derive their aesthetic qualities solely from tradition nor from Western Modernism or Postmodernism.

Subcellular localisation of proteins in fluorescent microscope images using a random forest

This paper presents a system that employs random forests to formulate a method for subcellular localisation of proteins. A random forest is an ensemble learner that grows classification trees. Each tree produces a classification decision, and an integrated output is calculated. The system classifies the protein-localisation patterns within fluorescent microscope images. 2D images of HeLa cells that include all major classes of subcellular structures, and the associated feature set are used. The performance of the developed system is compared against that of the support vector machine and decision tree approaches. Three experiments are performed to study the influence of the training and test set size on the performance of the examined methods. The calculated classification errors and execution times are presented and discussed. The lowest classification error (2.9%) has been produced by the developed system.

A random forest for lung nodule identification

A method is presented for identification of lung nodules. It includes three stages: image acquisition, background removal, and nodule detection. The first stage improves image quality. The second stage extracts long lobe regions. The third stage detects lung nodules. The method is based on the random forest learner. Training set contains nodule, non-nodule, and false-positive patterns. Test set contains randomly selected images. The developed method is compared against the support vector machine. True-positives of 100% and 85.9%, and false-positives of 1.27 and 1.33 per image were achieved by the developed method and the support vector machine, respectively.

Market makers v's the general public : a first look at S & P500 futures trade data

This paper considers 15 minute records of trading volume and traded prices coinciding with the reporting intervals required by the Commodity Futures Trading Commission. Records are extracted from trade records for market trade and also two way trade between market makers (CT1) and the general public (CT4) from January 1994 to June 2004. Futures price records are matched with S&P500 cash index price records. Simultaneous volatility models are specified and estimated to test trading volume to futures volatility lead/lag effects and also futures volatility to cash index volatility lead/lag effects. As we disaggregate from the market records to CT1 and CT4 records and further into year to year samples volume to futures volatility leading effects and also futures volatility to cash volatility leading effects dominate. The results raise important issues for risk management and dynamic hedging models employing intra-day trader data. A number of important issues for further analysis are also raised in this paper.

The Samuelson hypothesis in futures markets : an analysis using intraday data

This paper considers the Samuelson hypothesis, which argues that the futures price volatility increases as the futures contract approaches its expiration. Utilizing intraday data from 20 futures markets in six futures exchanges, we find strong support for the Samuelson hypothesis in agricultural futures. However, the Samuelson hypothesis does not hold for other futures contracts. We also provide supporting evidence that the ‘negative covariance’ hypothesis is the key factor for the empirical support of the Samuelson hypothesis. In addition, our findings remain largely unaltered even after we control for seasonality and liquidity effects.

Realized volatility and correlation in grain futures markets: testing for spillover effects

Fluctuations in commodity prices are a major concern to many market participants. This paper uses realized volatility methods to calculate daily volatility and correlation estimates for three grain futures prices (corn, soybean, and wheat). The realized volatility estimates exhibit properties consistent with the stylized facts observed in earlier studies. According to daily realized correlations and regression coefficients, the spot returns from the three grain futures are positively related. The realized estimates are then used to evaluate the degree of volatility transmission across grain futures prices. The impulse response analysis is conducted by fitting the vector autoregressive model to realized volatility and correlation estimates, using the bootstrap method for statistical inference. The results indicate that rich dynamic interactions exist among the volatilities and correlations across the grain futures markets.

Dispersion of information or market behaviour : general public trading in S & P 500 index futures

This paper considers 15 minute records of trading volume and traded prices coinciding with the reporting intervals required by the Commodity Futures Trading Commission. Records are extracted from trade records for two way trade between market makers (CTI1) and the general public (CTI4) from January 1994 to June 2004. Futures price records are matched with S&P500 cash index price records. Simultaneous volatility models are specified and estimated to test trading volume to futures volatility lead/lag effects and also futures volatility to cash index volatility lead/lag effects. There is evidence that existing theoretical models of the general public trading behaviour do not explain such behaviour in these very actively traded markets. These effects can depend more on market conditions than what is suggested in theoretical models.