Integrating high and moderate spatial resolution image data to estimate forest age structure

The collection of spatial information to quantify changes to the state and condition of the environment is a fundamental component of conservation or sustainable utilization of tropical and subtropical forests, Age is an important structural attribute of old-growth forests influencing biological diversity in Australia eucalypt forests. Aerial photograph interpretation has traditionally been used for mapping the age and structure of forest stands. However this method is subjective and is not able to accurately capture fine to landscape scale variation necessary for ecological studies. Identification and mapping of fine to landscape scale vegetative structural attributes will allow the compilation of information associated with Montreal Process indicators lb and ld, which seek to determine linkages between age structure and the diversity and abundance of forest fauna populations. This project integrated measurements of structural attributes derived from a canopy-height elevation model with results from a geometrical-optical/spectral mixture analysis model to map forest age structure at a landscape scale. The availability of multiple-scale data allows the transfer of high-resolution attributes to landscape scale monitoring. Multispectral image data were obtained from a DMSV (Digital Multi-Spectral Video) sensor over St Mary's State Forest in Southeast Queensland, Australia. Local scene variance levels for different forest tapes calculated from the DMSV data were used to optimize the tree density and canopy size output in a geometric-optical model applied to a Landsat Thematic Mapper (TU) data set. Airborne laser scanner data obtained over the project area were used to calibrate a digital filter to extract tree heights from a digital elevation model that was derived from scanned colour stereopairs. The modelled estimates of tree height, crown size, and tree density were used to produce a decision-tree classification of forest successional stage at a landscape scale. The results obtained (72% accuracy), were limited in validation, but demonstrate potential for using the multi-scale methodology to provide spatial information for forestry policy objectives (ie., monitoring forest age structure).

Determinants of hepato- and spleno-megaly in Hunan, China: cross-sectional survey data from areas endemic for schistosomiasis

In order to understand the determinants of schistosome-related hepato- and spleno-megaly better, 14 002 subjects aged 3-60 years (59% male; mean age =32 years) were randomly selected from 43 villages, all in Hunan province, China, where schistosomiasis caused by Schistosoma japonicum is endemic. The abdomen of each subject was examined along the mid-sternal (MSL) and mid-clavicular lines, for evidence of current hepato- and/or spleno-megaly, and a questionnaire was used to collect information on the medical history of each individual. Current infections with S. japonicum were detected by stool examination. Almost all (99.8%) of the subjects were ethnically Han by descent and most (77%) were engaged in farming. Although schistosomiasis appeared common (42% of the subjects claiming to have had the disease), only 45% of the subjects said they had received anti-schistosomiasis drugs. Overall, 1982 (14%) of the subjects had S. japonicum infections (as revealed by miracidium-hatching tests and/or Katon Katz smears) when examined and 22% had palpable hepatomegaly (i.e. enlargement of at least 3 cm along the MSL), although only 2.5% had any form of detectable splenomegaly (i.e. a Hackett's grade of at least 1). Multiple logistic regression revealed that male subjects, fishermen, farmers, subjects aged greater than or equal to 25 years, subjects with a history of schistosomiasis, and subjects who had had bloody stools in the previous 2 weeks were all at relatively high risk of hepato- and/or spleno-megaly. In areas moderately endemic for Schistosoma japonicum, occupational exposure and disease history appear to be good predictors of current disease status among older residents. These results reconfirm those reported earlier in the same region.

Matching prescription claims with medication data for nursing home residents: Implications for prescriber feedback, drug utilisation studies and selection of prescription claims database

Medication data retrieved from Australian Repatriation Pharmaceutical Benefits Scheme (RPBS) claims for 44 veterans residing in nursing homes and Pharmaceutical Benefits Scheme (PBS) claims for 898 nursing home residents were compared with medication data from nursing home records to determine the optimal time interval for retrieving claims data and its validity. Optimal matching was achieved using 12 weeks of RPBS claims data, with 60% of medications in the RPBS claims located in nursing home administration records, and 78% of medications administered to nursing home residents identified in RPBS claims. In comparison, 48% of medications administered to nursing home residents could be found in 12 weeks of PBS data, and 56% of medications present in PBS claims could be matched with nursing home administration records. RPBS claims data was superior to PBS, due to the larger number of scheduled items available to veterans and the veteran's file number, which acts as a unique identifier. These findings should be taken into account when using prescription claims data for medication histories, prescriber feedback, drug utilisation, intervention or epidemiological studies. (C) 2001 Elsevier Science Inc. All rights reserved.

A comparison between three and five factor models of Pakistani personality data

The Eysenck Personality Questionnaire-Revised (EPQ-R), the Eysenck Personality Profiler Short Version (EPP-S), and the Big Five Inventory (BFI-V4a) were administered to 135 postgraduate students of business in Pakistan. Whilst Extraversion and Neuroticism scales from the three questionnaires were highly correlated, it was found that Agreeableness was most highly correlated with Psychoticism in the EPQ-R and Conscientiousness was most highly correlated with Psychoticism in the EPP-S. Principal component analyses with varimax rotation were carried out. The analyses generally suggested that the five factor model rather than the three-factor model was more robust and better for interpretation of all the higher order scales of the EPQ-R, EPP-S, and BFI-V4a in the Pakistani data. Results show that the superiority of the five factor solution results from the inclusion of a broader variety of personality scales in the input data, whereas Eysenck's three factor solution seems to be best when a less complete but possibly more important set of variables are input. (C) 2001 Elsevier Science Ltd. All rights reserved.

Relating body mass index to figural stimuli: population-based normative data for Caucasians

OBJECTIVE: To establish body mass index (BMI) norms for standard figural stimuli using a large Caucasian population-based sample. In addition, we sought to determine the effectiveness of the figural stimuli to identify individuals as obese or thin. DESIGN: All Caucasian twins born in Virginia between 1915 and 1971 were identified by public birth record. In addition, 3347 individual twins responded to a letter published in the newsletter of the American Association of Retired Persons (AARP). All adult twins (aged 18 and over) from both of these sources and their family members were mailed a 16 page 'Health and Lifestyle' questionnaire. SUBJECTS: BMI and silhouette data were available on 16 728 females and 11 366 males ranging in age from 18- 100. MEASUREMENTS: Self-report information on height-weight, current body size, desired body size and a discrepancy score using standard figural stimuli. RESULTS: Gender- and age-specific norms are presented linking BMI to each of the figural stimuli. Additional norms for desired body size and discrepancy scores are also presented. Receiver operating curves (ROC) indicate that the figural stimuli are effective in classifying individuals as obese or thin. CONCLUSIONS: With the establishment of these norms, the silhouettes used in standard body image assessment can now be linked to BMI. Differences were observed between women and men in terms of desired body size and discrepancy scores, with women preferring smaller sizes. The figural stimuli are a robust technique for classifying individuals as obese or thin.

Laser-derived particle size data from CRP-3, Victoria Land Basin, Antarctica: Implications for sequence and seismic stratigraphy

Seven hundred and nineteen samples from throughout the Cainozoic section in CRP-3 were analysed by a Malvern Mastersizer laser particle analyser, in order to derive a stratigraphic distribution of grain-size parameters downhole. Entropy analysis of these data (using the method of Woolfe and Michibayashi, 1995) allowed recognition of four groups of samples, each group characterised by a distinctive grain-size distribution. Group 1, which shows a multi-modal distribution, corresponds to mudrocks, interbedded mudrock/sandstone facies, muddy sandstones and diamictites. Group 2, with a sand-grade mode but showing wide dispersion of particle size, corresponds to muddy sandstones, a few cleaner sandstones and some conglomerates. Group 3 and Group 4 are also sand-dominated, with better grain-size sorting, and correspond to clean, well-washed sandstones of varying mean grain-size (medium and fine modes, respectively). The downhole disappearance of Group 1, and dominance of Groups 3 and 4 reflect a concomitant change from mudrock- and diamictite-rich lithology to a section dominated by clean, well-washed sandstones with minor conglomerates. Progressive downhole increases in percentage sand and principal mode also reflect these changes. Significant shifts in grain-size parameters and entropy group membership were noted across sequence boundaries and seismic reflectors, as recognised in others studies.

Population pharmacokinetics of perhexiline from very sparse, routine monitoring data

Using NONMEM, the population pharmacokinetics of perhexiline were studied in 88 patients (34 F, 54 M) who were being treated for refractory angina. Their mean +/- SD (range) age was 75 +/- 9.9 years (46-92), and the length of perhexiline treatment was 56 +/- 77 weeks (0.3-416). The sampling time after a dose was 14.1 +/- 21.4 hours (0.5-200), and the perhexiline plasma concentrations were 0.39 +/- 0.32 mg/L (0.03-1.56). A one-compartment model with first-order absorption was fitted to the data using the first-order (FO) approximation. The best model contained 2 subpopulations (obtained via the $MIXTURE subroutine) of 77 subjects (subgroup A) and 11 subjects (subgroup B) that had typical values for clearance (CL/F) of 21.8 L/h and 2.06 L/h, respectively. The volumes of distribution (V/F) were 1470 L and 260 L, respectively, which suggested a reduction in presystemic metabolism in subgroup B. The interindividual variability (CV%) was modeled logarithmically and for CL/F ranged from 69.1% (subgroup A) to 86.3% (subgroup B). The interindividual variability in V/F was 111%. The residual variability unexplained by the population model was 28.2%. These results confirm and extend the existing pharmacokinetic data on perhexiline, especially the bimodal distribution of CL/F manifested via an inherited deficiency in hepatic and extrahepatic CYP2D6 activity.

Fitting a mixture model to three-mode three-way data with missing information

When the data consist of certain attributes measured on the same set of items in different situations, they would be described as a three-mode three-way array. A mixture likelihood approach can be implemented to cluster the items (i.e., one of the modes) on the basis of both of the other modes simultaneously (i.e,, the attributes measured in different situations). In this paper, it is shown that this approach can be extended to handle three-mode three-way arrays where some of the data values are missing at random in the sense of Little and Rubin (1987). The methodology is illustrated by clustering the genotypes in a three-way soybean data set where various attributes were measured on genotypes grown in several environments.

Exploratory spatial data analysis techniques for examining urban crime

Regional planners, policy makers and policing agencies all recognize the importance of better understanding the dynamics of crime. Theoretical and application-oriented approaches which provide insights into why and where crimes take place are much sought after. Geographic information systems and spatial analysis techniques, in particular, are proving to be essential or studying criminal activity. However, the capabilities of these quantitative methods continue to evolve. This paper explores the use of geographic information systems and spatial analysis approaches for examining crime occurrence in Brisbane, Australia. The analysis highlights novel capabilities for the analysis of crime in urban regions.

Probabilistic modelling of CO2 corrosion laboratory data using neural networks

The present paper addresses two major concerns that were identified when developing neural network based prediction models and which can limit their wider applicability in the industry. The first problem is that it appears neural network models are not readily available to a corrosion engineer. Therefore the first part of this paper describes a neural network model of CO2 corrosion which was created using a standard commercial software package and simple modelling strategies. It was found that such a model was able to capture practically all of the trends noticed in the experimental data with acceptable accuracy. This exercise has proven that a corrosion engineer could readily develop a neural network model such as the one described below for any problem at hand, given that sufficient experimental data exist. This applies even in the cases when the understanding of the underlying processes is poor. The second problem arises from cases when all the required inputs for a model are not known or can be estimated with a limited degree of accuracy. It seems advantageous to have models that can take as input a range rather than a single value. One such model, based on the so-called Monte Carlo approach, is presented. A number of comparisons are shown which have illustrated how a corrosion engineer might use this approach to rapidly test the sensitivity of a model to the uncertainities associated with the input parameters. (C) 2001 Elsevier Science Ltd. All rights reserved.