Agency problems and capital expenditure announcements

This article examines the market valuation of announcements of new capital expenditure. Prior research suggests that the firm's growth opportunities and cash flow position condition the market response. This study jointly examines the role of growth and cash flow, and the interaction between them. Using a new data set of Australian firms that avoids problems associated with expectations models, the results are remarkably strong and support a positive association between growth opportunities and the market valuation, in addition to supporting the role of free cash flow. The findings have implications for the relationship between general investment information and stock prices.

Further results on strongbox secured secret sharing schemes

We extend our earlier work on ways in which defining sets of combinatorial designs can be used to create secret sharing schemes. We give an algorithm for classifying defining sets or designs according to their security properties and summarise the results of this algorithm for many small designs. Finally, we discuss briefly how defining sets can be applied to variations of the basic secret sharing scheme.

An advanced regularization methodology for use in watershed model calibration

A calibration methodology based on an efficient and stable mathematical regularization scheme is described. This scheme is a variant of so-called Tikhonov regularization in which the parameter estimation process is formulated as a constrained minimization problem. Use of the methodology eliminates the need for a modeler to formulate a parsimonious inverse problem in which a handful of parameters are designated for estimation prior to initiating the calibration process. Instead, the level of parameter parsimony required to achieve a stable solution to the inverse problem is determined by the inversion algorithm itself. Where parameters, or combinations of parameters, cannot be uniquely estimated, they are provided with values, or assigned relationships with other parameters, that are decreed to be realistic by the modeler. Conversely, where the information content of a calibration dataset is sufficient to allow estimates to be made of the values of many parameters, the making of such estimates is not precluded by preemptive parsimonizing ahead of the calibration process. White Tikhonov schemes are very attractive and hence widely used, problems with numerical stability can sometimes arise because the strength with which regularization constraints are applied throughout the regularized inversion process cannot be guaranteed to exactly complement inadequacies in the information content of a given calibration dataset. A new technique overcomes this problem by allowing relative regularization weights to be estimated as parameters through the calibration process itself. The technique is applied to the simultaneous calibration of five subwatershed models, and it is demonstrated that the new scheme results in a more efficient inversion, and better enforcement of regularization constraints than traditional Tikhonov regularization methodologies. Moreover, it is argued that a joint calibration exercise of this type results in a more meaningful set of parameters than can be achieved by individual subwatershed model calibration. (c) 2005 Elsevier B.V. All rights reserved.

Isolation and characterization of microsatellite loci from Macadamia

Thirty-three microsatellite loci were isolated for the Australian rainforest tree Macadamia integrifolia. Genotyping across a test panel of 43 commercial cultivars generated an average polymorphic information content of 0.480. Five loci showed no polymorphism across cultivars. Significant linkage disequilibrium was detected in 10 pairwise comparisons, including two pairs of loci identified from the same clone sequence. The 33 microsatellite loci represent a significant tool for genome mapping and population genetic studies.

Analysis of stroke patients' and carers' reading ability and the content and design of written materials: Recommendations for improving written stroke information

Objective: This study (a) evaluated the reading ability of patients following stroke and their carers and the reading level and content and design characteristics of the written information provided to them, (b) explored the influence of sociodemographic and clinical characteristics on patients' reading ability, and (c) described an education package that provides well-designed information tailored to patients' and carers' informational needs. Methods: Fifty-seven patients and 12 carers were interviewed about their informational needs in an acute stroke unit. Their reading ability was assessed using the Rapid Estimate of Adult Literacy in Medicine (REALM). The written information provided to them in the acute stroke unit was analysed using the SMOG readability formula and the Suitability Assessment of Materials (SAM). Results: Thirteen (22.8%) patients and 5 (41.7%) carers had received written stroke information. The mean reading level of materials analysed was 11th grade while patients read at a mean of 7-8th grade. Most materials (89%) scored as only adequate in content and design. Patients with combined aphasia read significantly lower (4-6th grade) than other patients (p = 0.001). Conclusion: Only a small proportion of patients and carers received written materials about stroke and the readability level and content and design characteristics of most materials required improvement. Practice implications: When developing and distributing written materials about stroke, health professionals should consider the reading ability and informational needs of the recipients, and the reading level and content and design characteristics of the written materials. A computer system can be used to generate written materials tailored to the informational needs and literacy skills of patients and carers. (c) 2005 Elsevier Ireland Ltd. All rights reserved.

Making Fedora easier to implement with Fez: A free open source content model and workflow management front-end to Fedora

The University of Queensland, Australia has developed Fez, a world-leading user-interface and management system for Fedora-based institutional repositories, which bridges the gap between a repository and users. Christiaan Kortekaas, Andrew Bennett and Keith Webster will review this open source software that gives institutions the power to create a comprehensive repository solution without the hassle..

Long-term outcomes of genetic counseling in women at increased risk of developing hereditary breast cancer Information,

This multicenter study evaluated the impact of genetic counseling in 218 women at risk of developing hereditary breast cancer. Women were assessed prior to counseling and 12-month post-counseling using self-administered, mailed questionnaires. Compared to baseline, breast cancer genetics knowledge was increased significantly at follow-up. and greater increases in knowledge were associated with educational level. Breast cancer anxiety decreased significantly from baseline to follow-up, and these decreases were associated with improvements in perceived risk. A significant decrease in clinical breast examination was observed at the 12-month follow-up. Findings suggest that women with a family history of breast cancer benefit from attending familial cancer clinics as it leads to increases in breast cancer genetics knowledge and decreases in breast cancer anxiety. The lowered rates of clinical breast examination indicate that the content of genetic counseling may need to be reviewed to ensure that women receive and take away the right message. (C) 2001 Elsevier Science Ireland Ltd. All rights reserved.

Behavior of argon gas release from manganese oxide minerals as revealed by Ar-40/Ar-39 laser incremental heating analysis

Manganese oxides in association with paleo-weathering may provide significant insights into the multiple factors affecting the formation and evolution of weathering profiles, such as temperature, precipitation, and biodiversity. Laser probe step-heating analysis of supergene hollandite and cryptomelane samples collected from central Queensland, Australia, yield well-defined plateaus and consistent isochron ages, confirming the feasibility, dating very-fined supergene manganese oxides by Ar-40/(39) Ar technique. Two distinct structural sites hosting Ar isotopes can be identified in light of their degassing behaviors obtained by incremental heating analyses. The first site, releasing its gas fraction at the laser power 0.2-0.4 W, yields primarily Ar-40(atm), Ar-38(atm), and Ar-36(atm), (atmospheric Ar isotopes). The second sites yield predominantly Ar-40* (radiogenic Ar-40), Ar-39(K), and Ar-38(K) (nucleogenic components), at similar to0.5-1.0 W. There is no significant Ar gas released at the laser power higher than 1.0 W, indicating the breakdown of the tunnel sites hosting the radiogenic and nucleogenic components. The excellent match between the degassing behaviors of Ar-40*, Ar-39(K), and Ar-38(K) suggests that these isotopes occupy the same crystallographic sites and that Ar-39(K) loss from the tunnel site by recoil during neutron irradiation and/or bake-out procedure preceding isotopic analysis does not occur. Present investigation supports that neither the overwhelming atmospheric Ar-40 nor the very-fined nature of the supergene manganese oxides poses problems in extracting meaningful weathering geo-chronological information by analyzing supergene manganese oxides minerals.

Provitamin A carotenoid content of different cultivars of edible pandanus fruit

As part of an overall study to identify vitamin A-rich foods, a study was carried out in the Federated States of Micronesia (FSM) to provide information on production, acquisition, consumption and cultural acceptability of edible pandanus cultivars, Pandanus teetorius, and to identify their carotenoid content. Samples of five pandanus cultivars were collected and analyzed for alpha- and beta-carotene by HPLC. The results showed that the two cultivars with yellow fruit coloration contained low levels of carotenoids, while the orange fruits, which were also well liked as a food in the community, contained higher levels at maxima of 190 mug/100 g and 393 mug/100 g for alpha- and beta-carotene, respectively. Common patterns of intake when the fruit is available show that pandanus can provide a large proportion of estimated requirements of retinol equivalents. Local people were generally unaware that pandanus had health benefits, although the food was very popular. Nevertheless, key informants report that production had greatly decreased in recent years. To reverse this trend, those acceptable cultivars high in carotenoid content should be promoted both for their general enjoyment and their health benefits. (C) 2003 Elsevier Science Ltd. All rights reserved.

Searches and content of the OTseeker database: Informing research priorities

BACKGROUND. A strategic and prioritized approach to occupational therapy research is needed, particularly given the limited research funding available. Comparing occupational therapists' information needs with the research evidence available can potentially inform research debate within the profession. This study aimed to identify research topics most often sought by users of the OTseeker database and to compare these with the quantity of topics available in the database. METHOD. A random sample of keyword search terms submitted to OTseeker (n = 4,500) was coded according to diagnostic and intervention categories, and compared with the amount of research contained in OTseeker in 2004. RESULTS. Most frequently sought topics were relevant to the diagnostic categories of pediatric conditions (19%), neurology and neuromuscular disorders (17%), and mental health (17%). Most frequently sought intervention topics included modes of service delivery, sensory interventions, and physical modalities. Although many frequently sought topics had a correspondingly high volume of research in OTseeker, a few areas had very little content (e.g., fine motor skill acquisition, autistic spectrum disorder). This information is offered to inform discussions about research priorities and resource allocation for research within occupational therapy.

ICICLE: A semantic-based retrieval system for WWW images

In this paper, we present ICICLE (Image ChainNet and Incremental Clustering Engine), a prototype system that we have developed to efficiently and effectively retrieve WWW images based on image semantics. ICICLE has two distinguishing features. First, it employs a novel image representation model called Weight ChainNet to capture the semantics of the image content. A new formula, called list space model, for computing semantic similarities is also introduced. Second, to speed up retrieval, ICICLE employs an incremental clustering mechanism, ICC (Incremental Clustering on ChainNet), to cluster images with similar semantics into the same partition. Each cluster has a summary representative and all clusters' representatives are further summarized into a balanced and full binary tree structure. We conducted an extensive performance study to evaluate ICICLE. Compared with some recently proposed methods, our results show that ICICLE provides better recall and precision. Our clustering technique ICC facilitates speedy retrieval of images without sacrificing recall and precision significantly.

An Incremental EM-based Learning Approach for On-Line Prediction of Hospital Resource Utilization

Objective: Inpatient length of stay (LOS) is an important measure of hospital activity, health care resource consumption, and patient acuity. This research work aims at developing an incremental expectation maximization (EM) based learning approach on mixture of experts (ME) system for on-line prediction of LOS. The use of a batchmode learning process in most existing artificial neural networks to predict LOS is unrealistic, as the data become available over time and their pattern change dynamically. In contrast, an on-line process is capable of providing an output whenever a new datum becomes available. This on-the-spot information is therefore more useful and practical for making decisions, especially when one deals with a tremendous amount of data. Methods and material: The proposed approach is illustrated using a real example of gastroenteritis LOS data. The data set was extracted from a retrospective cohort study on all infants born in 1995-1997 and their subsequent admissions for gastroenteritis. The total number of admissions in this data set was n = 692. Linked hospitalization records of the cohort were retrieved retrospectively to derive the outcome measure, patient demographics, and associated co-morbidities information. A comparative study of the incremental learning and the batch-mode learning algorithms is considered. The performances of the learning algorithms are compared based on the mean absolute difference (MAD) between the predictions and the actual LOS, and the proportion of predictions with MAD < 1 day (Prop(MAD < 1)). The significance of the comparison is assessed through a regression analysis. Results: The incremental learning algorithm provides better on-line prediction of LOS when the system has gained sufficient training from more examples (MAD = 1.77 days and Prop(MAD < 1) = 54.3%), compared to that using the batch-mode learning. The regression analysis indicates a significant decrease of MAD (p-value = 0.063) and a significant (p-value = 0.044) increase of Prop(MAD

Incremental learning for interactive e-mail filtering

In this article, we propose a framework, namely, Prediction-Learning-Distillation (PLD) for interactive document classification and distilling misclassified documents. Whenever a user points out misclassified documents, the PLD learns from the mistakes and identifies the same mistakes from all other classified documents. The PLD then enforces this learning for future classifications. If the classifier fails to accept relevant documents or reject irrelevant documents on certain categories, then PLD will assign those documents as new positive/negative training instances. The classifier can then strengthen its weakness by learning from these new training instances. Our experiments’ results have demonstrated that the proposed algorithm can learn from user-identified misclassified documents, and then distil the rest successfully.