Robust ODF smoothing for accurate estimation of fiber orientation

Q-ball imaging was presented as a model free, linear and multimodal diffusion sensitive approach to reconstruct diffusion orientation distribution function (ODF) using diffusion weighted MRI data. The ODFs are widely used to estimate the fiber orientations. However, the smoothness constraint was proposed to achieve a balance between the angular resolution and noise stability for ODF constructs. Different regularization methods were proposed for this purpose. However, these methods are not robust and quite sensitive to the global regularization parameter. Although, numerical methods such as L-curve test are used to define a globally appropriate regularization parameter, it cannot serve as a universal value suitable for all regions of interest. This may result in over smoothing and potentially end up in neglecting an existing fiber population. In this paper, we propose to include an interpolation step prior to the spherical harmonic decomposition. This interpolation based approach is based on Delaunay triangulation provides a reliable, robust and accurate smoothing approach. This method is easy to implement and does not require other numerical methods to define the required parameters. Also, the fiber orientations estimated using this approach are more accurate compared to other common approaches.

Reduced order functional observers with application to partial state estimation of linear systems with input delay

Reduced order multi-functional observer design for multi-input multi-utput (MIMO) linear time-invariant (LTI) systems with constant delayed inputs is studied. This research is useful in the input estimation of LTI systems with actuator delay, as well as system monitoring and fault detection of these systems. Two approaches for designing an asymptotically stable functional observer for the system are proposed: delay-dependent and delay-free. The delay-dependent observer is infinite-dimensional, while the delay-free structure is finite-dimensional. Moreover, since the delay-free observer does not require any information on the time delay, it is more practical in real applications. However, the delay-dependent observer contains less restrictive assumptions and covers more variety of systems. The proposed observer design schemes are novel, simple to implement, and have improved numerical features compared to some of the other available approaches to design (unknown-input) functional observers. In addition, the proposed observers usually possess lower order than ordinary Luenberger observers, and the design schemes do not need the observability or detectability requirements of the system. The necessary and sufficient conditions of the existence of an asymptoticobserver in each scenario are explored. The extensions of the proposed observers to systems with multiple delayed-inputs are also discussed. Several numerical examples and simulation results are employed to support our theories.

Finding rule groups to classify high dimensional gene expression datasets

Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attracted bioinformatics researchers. Some approaches of machine learning are widely used to classify and mine biological datasets. However, many gene expression datasets are extremely high dimensionality, traditional machine learning methods can not be applied effectively and efficiently. This paper proposes a robust algorithm to find out rule groups to classify gene expression datasets. Unlike the most classification algorithms, which select dimensions (genes) heuristically to form rules groups to identify classes such as cancerous and normal tissues, our algorithm guarantees finding out best-k dimensions (genes), which are most discriminative to classify samples in different classes, to form rule groups for the classification of expression datasets. Our experiments show that the rule groups obtained by our algorithm have higher accuracy than that of other classification approaches

Touch it, feel it and experience it: developing professional IS skills using interview-style experiential simulations

The IS education field has made increasing use of computerised experiential simulations, but few attempts have been made to create an authentic learning environment that combines and balances elements of video-based computer simulation with real-life learning activities. This paper explores the design principles used to develop a CD-ROM simulation where learners use interviewing skills to elicit system requirements from simulated employees in an authentic context. The employees are videoed actors who converse with each other and with learners within a dynamic interaction model. The paper also describes how we combined this simulation with other teaching approaches such as in-class discussions, student team work, formal presentations, etc.

Linking attitudes and demographics in a tourist segmentation model : a two-stage approach

Segmentation has been widely studied in tourism research e.g. Dolnicar (2004). Dawley (2006) points that commonly used segmentation variables such as demographics lead to identifiable segments which are not actionable while other useful approaches e.g. psychographics, are actionable but not identifiable. The objective of this paper is to develop a two-stage linkage approach to segmentation whereby cluster analysis using psychographic variables is conducted within demographic group. Demographic groups are selected based on propensity to travel. This research utilizes data generated from a cross-sectional self-completed survey of 49,105 Australian respondents on travel and tourism. The managerial usefulness of this segmentation is assessed. Clearly segments can be directly linked both demographically and psychographically.

Finding rule groups to classify high dimensional gene expression datasets

Microarray data provides quantitative information about the transcription profile of cells. To analyse microarray datasets, methodology of machine learning has increasingly attracted bioinformatics researchers. Some approaches of machine learning are widely used to classify and mine biological datasets. However, many gene expression datasets are extremely high dimensionality, traditional machine learning methods cannot be applied effectively and efficiently. This paper proposes a robust algorithm to find out rule groups to classify gene expression datasets. Unlike the most classification algorithms, which select dimensions (genes) heuristically to form rules groups to identify classes such as cancerous and normal tissues, our algorithm guarantees finding out best-k dimensions (genes) to form rule groups for the classification of expression datasets. Our experiments show that the rule groups obtained by our algorithm have higher accuracy than that of other classification approaches.

Semantic and layered protein function prediction from PPI networks

Background The past few years have seen a rapid development in novel high-throughput technologies that have created large-scale data on protein-protein interactions (PPI) across human and most model species. This data is commonly represented as networks, with nodes representing proteins and edges representing the PPIs. A fundamental challenge to bioinformatics is how to interpret this wealth of data to elucidate the interaction of patterns and the biological characteristics of the proteins. One significant purpose of this interpretation is to predict unknown protein functions. Although many approaches have been proposed in recent years, the challenge still remains how to reasonably and precisely measure the functional similarities between proteins to improve the prediction effectiveness.

Results We used a Semantic and Layered Protein Function Prediction (SLPFP) framework to more effectively predict unknown protein functions at different functional levels. The framework relies on a new protein similarity measurement and a clustering-based protein function prediction algorithm. The new protein similarity measurement incorporates the topological structure of the PPI network, as well as the protein's semantic information in terms of known protein functions at different functional layers. Experiments on real PPI datasets were conducted to evaluate the effectiveness of the proposed framework in predicting unknown protein functions.

Conclusion The proposed framework has a higher prediction accuracy compared with other similar approaches. The prediction results are stable even for a large number of proteins. Furthermore, the framework is able to predict unknown functions at different functional layers within the Munich Information Center for Protein Sequence (MIPS) hierarchical functional scheme. The experimental results demonstrated that the new protein similarity measurement reflects more reasonably and precisely relationships between proteins.

Reducing unhealthy weight gain in Fijian adolescents : results of the Healthy Youth Healthy Communities study

Obesity is a significant problem among adolescents in Pacific populations. This paper reports on the outcomes of a 3-year obesity prevention study, Healthy Youth Healthy Communities, which was part of the Pacific Obesity Prevention in Communities project, undertaken with Fijian adolescents. The intervention was developed with schools and comprised social marketing, nutrition and physical activity initiatives and capacity building designed to reduce unhealthy weight, and the individual exposure period was just over 2-year duration. The evaluation incorporated a quasi-experimental, longitudinal design in seven intervention secondary schools near Suva (n = 874) and a matched sample of 11 comparison secondary schools from western Viti Levu (n = 2,062). There were significant differences between groups at baseline; the intervention group was shorter, weighed less, had a higher proportion of underweight and lower proportion of overweight, and better quality of life (Pediatric Quality of Life Inventory only). At follow-up, the intervention group had lower percentage body fat (-1.17) but also a lower increase in quality of life (Assessment of Quality of Life instrument: -0.02; Pediatric Quality of Life Inventory: -1.94) than the comparison group. There were no other differences in anthropometry, and behaviours’ changes showed a mixed pattern. In conclusion, this school-based health promotion programme lowered percentage body fat but did not reduce unhealthy weight gain or influence most obesity-promoting behaviours among Fijian adolescents. Despite growing evidence supporting the efficacy of community-based approaches to reduce obesity among children of European descent, findings from this study failed to demonstrate the efficacy of a community capacity-building approach among an adolescent sample drawn from a different sociocultural, economic and geographical context. Additional ‘top–down’ or other innovative approaches may be needed to reduce adolescent obesity in the Pacific.

Bias and precision of measures of survival gain from right-censored data

In cost-effectiveness analyses of drugs or health technologies, estimates of life years saved or quality-adjusted life years saved are required. Randomised controlled trials can provide an estimate of the average treatment effect; for survival data, the treatment effect is the difference in mean survival. However, typically not all patients will have reached the endpoint of interest at the close-out of a trial, making it difficult to estimate the difference in mean survival. In this situation, it is common to report the more readily estimable difference in median survival. Alternative approaches to estimating the mean have also been proposed. We conducted a simulation study to investigate the bias and precision of the three most commonly used sample measures of absolute survival gain - difference in median, restricted mean and extended mean survival - when used as estimates of the true mean difference, under different censoring proportions, while assuming a range of survival patterns, represented by Weibull survival distributions with constant, increasing and decreasing hazards. Our study showed that the three commonly used methods tended to underestimate the true treatment effect; consequently, the incremental cost-effectiveness ratio (ICER) would be overestimated. Of the three methods, the least biased is the extended mean survival, which perhaps should be used as the point estimate of the treatment effect to be inputted into the ICER, while the other two approaches could be used in sensitivity analyses. More work on the trade-offs between simple extrapolation using the exponential distribution and more complicated extrapolation using other methods would be valuable.

Retrospective analysis of cancer survival across South-Western Victoria in Australia

OBJECTIVE: This paper aims to describe cancer survival and examine association between survival and socio-demographic characteristics across Barwon South-Western region (BSWR) in Victoria, Australia. DESIGN: This study is based on the retrospective cohort database of patients accessing oncology services across BSWR. SETTING: Six rural and three urban hospital settings across the BSWR. PARTICIPANTS: The participants were patients who were diagnosed with cancer in 2009. MAIN OUTCOME MEASURES: Overall survival (OS) of participants was the main outcome measure. RESULTS: Total of 1778 eligible patients had four-year OS for all cancers combined of 59.7% (95% CI, 57.4-62.0). Improved OS was observed for patients in the upper socio-economic tertile (64.2%; 95% CI, 60.9-67.5) compared to the middle (59.3%; 95% CI, 55.5-63.1) and lowest tertiles (49.6%; 95% CI, 44.2-54.9) (P < 0.01). On multivariate analyses, higher socio-economic status remained a significant predictor of OS adjusting for gender, remoteness and age (HR [hazard ratio] 0.81; 95% CI 0.74-0.89; P < 0.01). Remoteness was significantly associated with improved OS after adjusting for age, gender and socio-economic status (HR 0.86; 95% CI, 0.77-0.97; P = 0.01). Older age ≥70 years compared to <70 years conferred inferior OS (HR 3.08; 95% CI, 2.64-3.59; P < 0.01). CONCLUSIONS: Our study confirmed improved survival outcomes for patients of higher socio-economic status and younger age. Future research to explain the unexpected survival benefit in patients who lived in more remote areas should examine factors including the correlation between geographical residence and eventual treatment facility as well as compare the BSWR care model to other regions' approaches.

Testing the focal species approach to making conservation decisions for species persistence

Aim: Most risk assessments and decisions in conservation are based on surrogate approaches, where a group of species or environmental indicators are selected as proxies for other aspects of biodiversity. In the focal species approach, a suite of species is selected based on life history characteristics, such as dispersal limitation and area requirements. Testing the validity of the focal species concept has proved difficult, due to a lack of theory justifying the underlying framework, explicit objectives and measures of success. We sought to understand the conditions under which the focal species concept has merit for conservation decisions. Location: Our model system comprised 10 vertebrate species in 39 patches of native forest embedded in pine plantation in New South Wales, Australia. Methods: We selected three focal species based on ecological traits. We used a multiple-species reserve selection method that minimizes the expected loss of species, by estimating the risk of extinction with a metapopulation model. We found optimal reserve solutions for multiple species, including all 10 species, the three focal species, for all possible combinations of three species, and for each species individually. Results: Our case study suggests that the focal species approach can work: the reserve system that minimized the expected loss of the focal species also minimized the expected species loss in the larger set of 10 species. How well the solution would perform for other species and given landscape dynamics remains unknown. Main conclusions: The focal species approach may have merit as a conservation short cut if placed within a quantitative decision-making framework, where the aspects of biodiversity for which the focal species act as proxies are explicitly defined, and success is determined by whether the use of the proxy results in the same decision. Our methods provide a framework for testing other surrogate approaches used in conservation decision-making and risk assessment. © 2013 John Wiley & Sons Ltd.

Anisotropy for metals in non-associated flow plasticity

 A constitutive model based on Non-Associated Flow rule is implemented numerically and is shown to be capable of accurate predictions of anisotropy driven phenomena, observed during the forming processes of thin sheet metals, in a more efficient manner than other traditional approaches based on Associated Flow Rule.

Effect of elastic modulus and poisson's ratio on guided wave dispersion using transversely isotropic material modelling

Timber poles are commonly used for telecommunication and power distribution networks, wharves or jetties, piling or as a substructure of short span bridges. Most of the available techniques currently used for non-destructive testing (NDT) of timber structures are based on one-dimensional wave theory. If it is essential to detect small sized damage, it becomes necessary to consider guided wave (GW) propagation as the behaviour of different propagating modes cannot be represented by one-dimensional approximations. However, due to the orthotropic material properties of timber, the modelling of guided waves can be complex. No analytical solution can be found for plotting dispersion curves for orthotropic thick cylindrical waveguides even though very few literatures can be found on the theory of GW for anisotropic cylindrical waveguide. In addition, purely numerical approaches are available for solving these curves. In this paper, dispersion curves for orthotropic cylinders are computed using the scaled boundary finite element method (SBFEM) and compared with an isotropic material model to indicate the importance of considering timber as an anisotropic material. Moreover, some simplification is made on orthotropic behaviour of timber to make it transversely isotropic due to the fact that, analytical approaches for transversely isotropic cylinder are widely available in the literature. Also, the applicability of considering timber as a transversely isotropic material is discussed. As an orthotropic material, most material testing results of timber found in the literature include 9 elastic constants (three elastic moduli and six Poisson's ratios), hence it is essential to select the appropriate material properties for transversely isotropic material which includes only 5 elastic constants. Therefore, comparison between orthotropic and transversely isotropic material model is also presented in this article to reveal the effect of elastic moduli and Poisson's ratios on dispersion curves. Based on this study, some suggestions are proposed on selecting the parameters from an orthotropic model to transversely isotropic condition.

37° Sur a 19° Norte: Fotografía contemporánea de Australia

Curatorial considerations, aims and objectives:The title for this exhibition (37 ° South to 19 ° North) refers to the Latitude of Melbourne, Australia and Cuernavaca, Mexico.My curatorial objective for making such a reference to the geographical was to invoke a sense of both distance and connection between the two locations of Australia and Mexico and to also create a sense of sharing, not only between our distant landscapes and cultures but also between the feelings and emotions that we all experience in response to the places in which we live out the moments which make up our daily lives.In developing this project I considered the work of more than 35 contemporary Australian photographers and finally selected 15 photographers (including myself). Most of these artists have or have had close connection to Melbourne and to the southern/eastern line of Australian continent. The final selection ranged from Hobart to Maroochydore and one artist who had lived in Melbourne for many years but was now living in Mexico. These photographers (and the specific works) were selected because their long term creative practice captures a sense of location (place and space) with a deep introspective sensibility which I feel offers a viewer a personal and softly spoken vision of some particular aspect of an Australian location, be that exterior landscape or interior place and a sense of unique connection to such places. These images are not documents but rather representations of feelings, stories, memories and dreams which emerge in the milieu of our inhabitants.In selecting the works, careful consideration was also given to diversity of approaches to photographic practice in conjunction to thematic content. Formats and media included black and white, pin hole photography, toy camera, large format (both 4” x 5” and 10”x 8”), phone camera, various digital camera images and other experimental approaches. The local art scene in Cuernavaca is very strong and there is a strong interest in photography. This is partially due to the number of local arts schools and universities which offer studies in photography as well as the political dimension regarding Mexican art in general - as a tool of both political media, reportage and documentary work, photography is a significant medium for many of the people who would be visiting the exhibition. I therefore felt it was important to address the diversity of approaches to the medium which are currently being explored by Australian practitioners.The City Museum of Cuernavaca provided two large walls and some smaller sections of side walls on both the grounds level and the upper level of the main museum galleries for exhibition.The works were arranged with a simple thematic structure. Top level, left to right, then bottom level, left to right starting with images which presented a sense of wilderness and landscape (which were also quite abstract and reductive) to more representational landscape images moving to landscape with small figures (people) emerging within the images (Ash Kerr) to landscapes with larger figures and the emerging presence of man-made elements to urban landscapes and then to interior urban scapes and finally to interior locations with people and finally finishing on the metaphorical image by Harry Nankin of Bogong Moths and the politics of climate change. (It is also interesting to note that the migration path of the Bongong moth matches well the distribution of the artists selected for this project)Broadly speaking the images started outside with broad landscape to intimate interior locations. With these works a great deal of personal content from each photographer was presented. Most artists chose to present 3 large format images while some only presented 2 images. Other graphic and visual elements were considered in the final placement of the images.It must also be noted that the artists selected ranged broadly from very highly established and significant local artists to mid-career/younger establishing artist to some lesser known and emerging artists. From a curatorial perspective I feel this is offers the possibility of what I shall term, a more balanced representation of the local Australian practice and it provides a context in which both established and emerging artists / works must engage on a dialogue, within the exhibition. I believe it also placing the curatorial premise on the strength of the work rather than on whom the artists are and their status. It also supports the younger emerging artists and provides a less formal and predictable outcome for the established artists and for as a collective presentation as a whole.

Interpreting behaviors from accelerometry: a method combining simplicity and objectivity.

Quantifying the behavior of motile, free-ranging animals is difficult. The accelerometry technique offers a method for recording behaviors but interpretation of the data is not straightforward. To date, analysis of such data has either involved subjective, study-specific assignments of behavior to acceleration data or the use of complex analyses based on machine learning. Here, we present a method for automatically classifying acceleration data to represent discrete, coarse-scale behaviors. The method centers on examining the shape of histograms of basic metrics readily derived from acceleration data to objectively determine threshold values by which to separate behaviors. Through application of this method to data collected on two distinct species with greatly differing behavioral repertoires, kittiwakes, and humans, the accuracy of this approach is demonstrated to be very high, comparable to that reported for other automated approaches already published. The method presented offers an alternative to existing methods as it uses biologically grounded arguments to distinguish behaviors, it is objective in determining values by which to separate these behaviors, and it is simple to implement, thus making it potentially widely applicable. The R script coding the method is provided.