A Bayesian model predicts the response of axons to molecular gradients

Axon guidance by molecular gradients plays a crucial role in wiring up the nervous system. However, the mechanisms axons use to detect gradients are largely unknown. We first develop a Bayesian “ideal observer” analysis of gradient detection by axons, based on the hypothesis that a principal constraint on gradient detection is intrinsic receptor binding noise. Second, from this model, we derive an equation predicting how the degree of response of an axon to a gradient should vary with gradient steepness and absolute concentration. Third, we confirm this prediction quantitatively by performing the first systematic experimental analysis of how axonal response varies with both these quantities. These experiments demonstrate a degree of sensitivity much higher than previously reported for any chemotacting system. Together, these results reveal both the quantitative constraints that must be satisfied for effective axonal guidance and the computational principles that may be used by the underlying signal transduction pathways, and allow predictions for the degree of response of axons to gradients in a wide variety of in vivo and in vitro settings.

Mortality, fertility, and persistent income inequality

Many developing countries are plagued by persistent inequality in income distribution. While a growing body of economic-demographic literature emphasizes differential fertility channel, this paper investigates differential child mortality--differences in child mortality across income groups--as a critical link through which income inequality persists. Using an overlapping generations model in which both child mortality and fertility are endogenously determined by parental choice, this paper demonstrates that differential child mortality and its interaction with differential fertility may generate an "income inequality trap." The trap is characterized by higher child mortality and lower degree of skill formation among the poorer households. The model can also explain the behavior of aggregate fertility and mortality rates for countries at various stages of development, consonant with patterns of demographic transition. The results indicate that provision of public health that raises the productivity of private health spending may be an effective way to reduce income inequality

Improving the provision of learning assistance services in higher education

This study is motivated by the need to look continually for ways to improve Griffith University's learning assistance services so that they meet the changed needs of stakeholders and are at the same time cost-effective and efficient. This study uses the conceptual tools of cultural-historical activity theory and expansive visibilisation to investigaate the developmenet and transformation of learning assistance services at Griffith University, one of Australia's largest mult-campus universities.

Application of higher order spectra to identify epileptic EEG

Epilepsy is characterized by the spontaneous and seemingly unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic system that detects seizure onsets would allow patients or the people near them to take appropriate precautions, and could provide more insight into this phenomenon. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, we made a comparative study of the performance of Gaussian mixture model (GMM) and Support Vector Machine (SVM) classifiers using the features derived from HOS and from the power spectrum. Results show that the selected HOS based features achieve 93.11% classification accuracy compared to 88.78% with features derived from the power spectrum for a GMM classifier. The SVM classifier achieves an improvement from 86.89% with features based on the power spectrum to 92.56% with features based on the bispectrum.

Pattern recognition using invariants defined from higher order spectra : 2-D image inputs

A new algorithm for extracting features from images for object recognition is described. The algorithm uses higher order spectra to provide desirable invariance properties, to provide noise immunity, and to incorporate nonlinearity into the feature extraction procedure thereby allowing the use of simple classifiers. An image can be reduced to a set of 1D functions via the Radon transform, or alternatively, the Fourier transform of each 1D projection can be obtained from a radial slice of the 2D Fourier transform of the image according to the Fourier slice theorem. A triple product of Fourier coefficients, referred to as the deterministic bispectrum, is computed for each 1D function and is integrated along radial lines in bifrequency space. Phases of the integrated bispectra are shown to be translation- and scale-invariant. Rotation invariance is achieved by a regrouping of these invariants at a constant radius followed by a second stage of invariant extraction. Rotation invariance is thus converted to translation invariance in the second step. Results using synthetic and actual images show that isolated, compact clusters are formed in feature space. These clusters are linearly separable, indicating that the nonlinearity required in the mapping from the input space to the classification space is incorporated well into the feature extraction stage. The use of higher order spectra results in good noise immunity, as verified with synthetic and real images. Classification of images using the higher order spectra-based algorithm compares favorably to classification using the method of moment invariants

Shape discrimination using invariants defined from higher-order spectra

An approach to pattern recognition using invariant parameters based on higher-order spectra is presented. In particular, bispectral invariants are used to classify one-dimensional shapes. The bispectrum, which is translation invariant, is integrated along straight lines passing through the origin in bifrequency space. The phase of the integrated bispectrum is shown to be scale- and amplification-invariant. A minimal set of these invariants is selected as the feature vector for pattern classification. Pattern recognition using higher-order spectral invariants is fast, suited for parallel implementation, and works for signals corrupted by Gaussian noise. The classification technique is shown to distinguish two similar but different bolts given their one-dimensional profiles

A general procedure for the derivation of principal domains of higher-order spectra

A general procedure to determine the principal domain (i.e., nonredundant region of computation) of any higher-order spectrum is presented, using the bispectrum as an example. The procedure is then applied to derive the principal domain of the trispectrum of a real-valued, stationary time series. These results are easily extended to compute the principal domains of other higher-order spectra

Position, rotation, and scale invariant recognition of images using higher-order spectra

A new approach to recognition of images using invariant features based on higher-order spectra is presented. Higher-order spectra are translation invariant because translation produces linear phase shifts which cancel. Scale and amplification invariance are satisfied by the phase of the integral of a higher-order spectrum along a radial line in higher-order frequency space because the contour of integration maps onto itself and both the real and imaginary parts are affected equally by the transformation. Rotation invariance is introduced by deriving invariants from the Radon transform of the image and using the cyclic-shift invariance property of the discrete Fourier transform magnitude. Results on synthetic and actual images show isolated, compact clusters in feature space and high classification accuracies

A transition program in first year law : adopting the First Year Curriculum Principles

The First Year Curriculum Principles espouse a student-focused consistent and explicit curriculum, acknowledging diversity and the need to scaffold skills and learning. Commencing law students are no different to other first year students in that they must deal with changes in teaching and learning approaches and expectations. As well as the generic issues of transition, law students must grapple with learning the skills which are necessary for the study of law from the very start of their degree. A transition program at the commencement of a law degree as part of a planned first year curriculum provides an opportunity to introduce students to the study of law, the requisite skills as well as assist with transition to tertiary education.

Theorising a model for teaching and assessing reflective learning in higher education

The importance of reflection in higher education, and across disciplinary fields is widely recognised; it is generally included in university graduate attributes, professional standards and program objectives. Furthermore, reflection is commonly embedded into assessment requirements in higher education subjects, often without necessary scaffolding or clear expectations for students. Despite the rhetoric around the importance of reflection for ongoing learning, there is scant literature on any systematic, developmental approach to teaching reflective learning across higher education programs/courses. Given that professional or academic reflection is not intuitive, and requires specific pedagogic intervention to do well, a program/course-wide approach is essential. This paper draws on current literature to theorise a new, transferable and customisable model for teaching and assessing reflective learning across higher education, which foregrounds and explains the pedagogic field of higher education as a multi-dimensional space. We argue that explicit and strategic pedagogic intervention, supported by dynamic resources, is necessary for successful, broad-scale approaches to reflection in higher education.

Conceptualising and teaching discursive and performative reflection in higher education

The importance of reflection in higher education, and across disciplinary fields is widely recognised. It is generally embedded in university graduate attributes, professional standards and course objectives. Furthermore, reflection is commonly included in assessment requirements in higher education subjects, often without necessary scaffolding or clear expectations for students. It is essential that academic staff have substantive knowledge and clear expectations about the aims of reflective activities, the most effective mode of representation, and appropriate teaching strategies to support students in deep, critical reflection. The paper argues the case for reflection to be represented in different modes, using discursive (language) or performative (symbolic practice) forms of expression according to disciplinary context and individual communicative strengths. It introduces key discursive and expressive elements that constitute different modes of representation in reflective tasks. This functional analysis of textual elements provides explicit knowledge for teaching and assessing multiple modes of reflection in higher education.

An exploration of shared services types in higher education

The emerging global Higher Education (HE) market challenges all universities to reconsider their mission, in order to function effectively and efficiently, and to be responsive to changing marketplace demands. Universities are considering cooperating or sharing in a wide range of areas, in order to achieve sought after cost savings and improvements in performance.Studies suggest that a wide range of services could potentially be shared across Higher Education Institutions (HEIs),offering several potential benefits. While there are many individual documented examples of how shared services have been applied in the Higher Education sector, there has been little synthesis, conceptualization or discussion (in general or in the HE sector) around the different types of possible shared services options and how they are structured. A deeper understanding of potential types of sharing arrangements will be of value to those universities considering shared services, implementing shared services, and managing shared services. Through analysis of 36 documented case studies of shared services in HE, this study sought to synthesize a typology of sharing arrangements. An inductive approach was used to identify the core differentiating dimensions. The findings present eight types of sharing arrangements that occur in the HE sector, with descriptions and examples from the case studies observed.

Prevalence of malnutrition in Parkinson's disease : a systematic review

Parkinson's disease (PD) patients may be at higher risk of malnutrition because of the symptoms associated with the disease and the side effects of the medication used to manage it. A decline in nutritional status is associated with many adverse outcomes related to health and quality of life. It is not clear, however, to what extent this population is currently affected by malnutrition. The objective of this review was to systematically assess the methodology and outcomes of studies reporting the prevalence of malnutrition in PD patients. Studies that attempted to classify participants with PD into nutritional risk and/or malnutrition categories using body mass index, weight change, anthropometric measures, and nutritional screening and assessment scores were included. The prevalence of malnutrition ranged from 0% to 24% in PD patients, while 3–60% of PD patients were reported to be at risk of malnutrition. There was a large degree of variation among studies in the methods chosen, the definition of malnutrition using those methods, and the detail in which the methodological protocols were reported. The true extent of malnutrition in the PD population has yet to be accurately quantified. It is important, however, to screen for malnutrition at the time of PD diagnosis.

Ocular characteristics in myopic anisometropia

PURPOSE: To investigate the interocular symmetry of ocular optical, biometric and biomechanical characteristics between the more and less ametropic eyes of myopic anisometropes. METHODS: Thirty-four young, healthy myopic anisometropic adults (≥ 1 D spherical equivalent difference between eyes) without amblyopia or strabismus were recruited. A range of biometric and optical parameters were measured in the more and less ametropic eye of each subject including; axial length, ocular aberrations, intraocular pressure and corneal topography, thickness and biomechanics. Morphology of the anterior eye in primary and downward gaze was examined using custom software analysis of high resolution digital images. Ocular sighting dominance was assessed using the hole-in-the-card test. RESULTS: Mean absolute spherical equivalent anisometropia was 1.74 ± 0.74 D. There was a strong correlation between the degree of anisometropia and the interocular difference in axial length (r = 0.81, p < 0.001). The more and less ametropic fellow eyes displayed a high degree of interocular symmetry for the majority of biometric, biomechanical and optical parameters measured. When the level of anisometropia exceeded 1.75 D (n = 10), the more myopic eye was the dominant sighting eye in nine of these ten subjects. Subjects with greater levels of anisometropia (> 1.75 D) also showed high levels of correlation between the dominant and non-dominant eyes in their biometric, biomechanical and optical characteristics. CONCLUSIONS: Although significantly different in axial length, anisometropic eyes display a high degree of interocular symmetry for a range of anterior eye biometrics and optical parameters. For higher levels of anisometropia, the more myopic eye tends to be the dominant sighting eye.