Peripheral ocular aberrations in mild and moderate keratoconus

Purpose: To investigate the influence of keratoconus on peripheral ocular aberrations. Methods: Aberrations of 7 mild and 5 moderate keratoconics were determined over a 42°horizontal x 32° vertical visual field with a modified COAS-HD aberrometer. Control data were obtained from an emmetropic group. Results: Most aberrations in keratoconics showed field dependence predominately along the vertical meridian. Mean spherical equivalent M, oblique astigmatism J45 and regular astigmatism J180 refraction components and total root mean square aberrations (excluding defocus) had high magnitudes in the inferior visual field. The rates of change of aberrations were higher in moderate than in mild keratoconics. Coma was the dominant peripheral higher-order aberration in both emmetropes and keratoconics; for the latter it had high magnitudes in the centre and periphery of the visual field. Conclusion: Greater rates of change of aberrations across the visual field occurred for the keratoconic groups than for the emmetropic control group. Moderate keratoconics had more rapid changes in, and higher magnitudes of aberrations across the visual field than mild keratoconics. The dominant higher-order aberration for the keratoconics across the visual field was vertical coma.

Anxiety and Aboriginal and Torres Strait Islander young people

This chapter outlines issues of excessive anxiety in Indigenous youth. It describes what an anxiety disorder is and its consequences and how Indigenous youth seem to be at risk for developing such disorders. Issues concerning the delivery of traditional prevention and intervention programs are discussed and possible interventions are provided.

Differential roles of the pRb and Arf/p53 pathways in murine naevus and melanoma genesis

We report on a systematic analysis of genotype-specific melanocyte (MC) UVR responses in transgenic mouse melanoma models along with tumour penetrance and comparative histopathology. pRb or p53 pathway mutations cooperated with NrasQ61K to transform MCs. We previously reported that MCs migrate from the follicular outer root sheath into the epidermis after neonatal UVR. Here, we found that Arf or p53 loss markedly diminished this response. Despite this, mice carrying these mutations developed melanoma with very early age of onset after neonatal UVR. Cdk4R24C did not affect the MC migration. Instead, independent of UVR exposure, interfollicular dermal MCs were more prevalent in Cdk4R24C mice. Subsequently, in adulthood, these mutants developed dermal MC proliferations reminiscent of superficial congenital naevi. Two types of melanoma were observed in this model. The location and growth pattern of the first was consistent with derivation from the naevi, while the second appeared to be of deep dermal origin. In animals carrying the Arf or p53 defects, no naevi were detected, with all tumours ostensibly skipping the benign precursor stage in progression.

Evaluation of spectral and texture features for object-based vegetation species classification using Support Vector Machines

The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.

Empirical comparison of machine learning algorithms for image texture classification with application to vegetation management in power line corridors

This paper reports on the empirical comparison of seven machine learning algorithms in texture classification with application to vegetation management in power line corridors. Aiming at classifying tree species in power line corridors, object-based method is employed. Individual tree crowns are segmented as the basic classification units and three classic texture features are extracted as the input to the classification algorithms. Several widely used performance metrics are used to evaluate the classification algorithms. The experimental results demonstrate that the classification performance depends on the performance matrix, the characteristics of datasets and the feature used.

Advances in vegetation management for power line corridor monitoring using aerial remote sensing techniques

This paper presents a comprehensive discussion of vegetation management approaches in power line corridors based on aerial remote sensing techniques. We address three issues 1) strategies for risk management in power line corridors, 2) selection of suitable platforms and sensor suite for data collection and 3) the progress in automated data processing techniques for vegetation management. We present initial results from a series of experiments and, challenges and lessons learnt from our project.

Color and texture feature fusion using kernel PCA with application to object-based vegetation species classification

A good object representation or object descriptor is one of the key issues in object based image analysis. To effectively fuse color and texture as a unified descriptor at object level, this paper presents a novel method for feature fusion. Color histogram and the uniform local binary patterns are extracted from arbitrary-shaped image-objects, and kernel principal component analysis (kernel PCA) is employed to find nonlinear relationships of the extracted color and texture features. The maximum likelihood approach is used to estimate the intrinsic dimensionality, which is then used as a criterion for automatic selection of optimal feature set from the fused feature. The proposed method is evaluated using SVM as the benchmark classifier and is applied to object-based vegetation species classification using high spatial resolution aerial imagery. Experimental results demonstrate that great improvement can be achieved by using proposed feature fusion method.

Reduction of environmental effects of civil aircraft through multi-objective flight plan optimisation

With rising environmental alarm, the reduction of critical aircraft emissions including carbon dioxides (CO2) and nitrogen oxides (NOx) is one of most important aeronautical problems. There can be many possible attempts to solve such problem by designing new wing/aircraft shape, new efficient engine, etc. The paper rather provides a set of acceptable flight plans as a first step besides replacing current aircrafts. The paper investigates a green aircraft design optimisation in terms of aircraft range, mission fuel weight (CO2) and NOx using advanced Evolutionary Algorithms coupled to flight optimisation system software. Two multi-objective design optimisations are conducted to find the best set of flight plans for current aircrafts considering discretised altitude and Mach numbers without designing aircraft shape and engine types. The objectives of first optimisation are to maximise range of aircraft while minimising NOx with constant mission fuel weight. The second optimisation considers minimisation of mission fuel weight and NOx with fixed aircraft range. Numerical results show that the method is able to capture a set of useful trade-offs that reduce NOx and CO2 (minimum mission fuel weight).

Melanocyte homeostasis in vivo tolerates Rb1 loss in a developmentally independent fashion

There has been uncertainty regarding the precise role that the pocket protein Rb1 plays in murine melanocyte homeostasis. It has been reported that the TAT-Cre mediated loss of exon 19 from a floxed Rb1 allele causes melanocyte apoptosis in vivo and in vitro. This is at variance with other findings showing, either directly or indirectly, that Rb1 loss in melanocytes has no noticeable effect in vivo, but in vitro leads to a semi-transformed phenotype. In this study, we show that Rb1-null melanocytes lacking exon 19 do not undergo apoptosis and survive both in vitro and in vivo, irrespective of the developmental stage at which Cre-mediated ablation of the exon occurs. Further, Rb1 loss has no serious long-term ramifications on melanocyte homeostasis in vivo, with Rb1-null melanocytes being detected in the skin after numerous hair cycles, inferring that the melanocyte stem cell population carrying the Cre-mediated deletion is maintained. Consequently, whilst Rb1 loss in the melanocyte is able to alter cellular behaviour in vitro, it appears inconsequential with respect to melanocyte homeostasis in the mouse skin.

A synthesizable hardware evolutionary algorithm design for unmanned aerial system real-time path planning

The main objective of this paper is to detail the development of a feasible hardware design based on Evolutionary Algorithms (EAs) to determine flight path planning for Unmanned Aerial Vehicles (UAVs) navigating terrain with obstacle boundaries. The design architecture includes the hardware implementation of Light Detection And Ranging (LiDAR) terrain and EA population memories within the hardware, as well as the EA search and evaluation algorithms used in the optimizing stage of path planning. A synthesisable Very-high-speed integrated circuit Hardware Description Language (VHDL) implementation of the design was developed, for realisation on a Field Programmable Gate Array (FPGA) platform. Simulation results show significant speedup compared with an equivalent software implementation written in C++, suggesting that the present approach is well suited for UAV real-time path planning applications.

Control of aircraft for inspection of linear infrastructure

Inspection aircraft equipped with cameras and other sensors are routinely used for asset location, inspection, monitoring and hazard identification of oil-gas pipelines, roads, bridges and power transmission grids. This paper is concerned with automated flight of fixed-wing inspection aircraft to track approximately linear infrastructure. We propose a guidance law approach that seeks to maintain aircraft trajectories with desirable position and orientation properties relative to the infrastructure under inspection. Furthermore, this paper also proposes the use of an adaptive maneuver selection approach, in which maneuver primitives are adaptively selected to improve the aircraft’s attitude behaviour. We employ an integrated design methodology particularly suited for an automated inspection aircraft. Simulation studies using full nonlinear semi-coupled six degree-of-freedom equations of motion are used to illustrate the effectiveness of the proposed guidance and adaptive maneuver selection approaches in realistic flight conditions. Experimental flight test results are given to demonstrate the performance of the design.

Making sense of brain tumour: A qualitative investigation of personal and social processes of adjustment

This study investigated personal and social processes of adjustment at different stages of illness for individuals with brain tumour. A purposive sample of 18 participants with mixed tumour types (9 benign and 9 malignant) and 15 family caregivers was recruited from a neurosurgical practice and a brain tumour support service. In-depth semi-structured interviews focused on participants’ perceptions of their adjustment, including personal appraisals, coping and social support since their brain tumour diagnosis. Interview transcripts were analysed thematically using open, axial and selective coding techniques. The primary theme that emerged from the analysis entailed “key sense making appraisals”, which was closely related to the following secondary themes: (1) Interactions with those in the healthcare system, (2) reactions and support from the personal support network, and (3) a diversity of coping efforts. Adjustment to brain tumour involved a series of appraisals about the illness that were influenced by interactions with those in the healthcare system, reactions and support from people in their support network, and personal coping efforts. Overall, the findings indicate that adjustment to brain tumour is highly individualistic; however, some common personal and social processes are evident in how people make sense of and adapt to the illness over time. A preliminary framework of adjustment based on the present findings and its clinical relevance are discussed. In particular, it is important for health professionals to seek to understand and support individuals’ sense-making processes following diagnosis of brain tumour.

Fixed-wing attitude estimation using temporal tracking of the horizon and optical flow

In this paper, a method has been developed for estimating pitch angle, roll angle and aircraft body rates based on horizon detection and temporal tracking using a forward-looking camera, without assistance from other sensors. Using an image processing front-end, we select several lines in an image that may or may not correspond to the true horizon. The optical flow at each candidate line is calculated, which may be used to measure the body rates of the aircraft. Using an Extended Kalman Filter (EKF), the aircraft state is propagated using a motion model and a candidate horizon line is associated using a statistical test based on the optical flow measurements and the location of the horizon. Once associated, the selected horizon line, along with the associated optical flow, is used as a measurement to the EKF. To test the accuracy of the algorithm, two flights were conducted, one using a highly dynamic Uninhabited Airborne Vehicle (UAV) in clear flight conditions and the other in a human-piloted Cessna 172 in conditions where the horizon was partially obscured by terrain, haze and smoke. The UAV flight resulted in pitch and roll error standard deviations of 0.42◦ and 0.71◦ respectively when compared with a truth attitude source. The Cessna flight resulted in pitch and roll error standard deviations of 1.79◦ and 1.75◦ respectively. The benefits of selecting and tracking the horizon using a motion model and optical flow rather than naively relying on the image processing front-end is also demonstrated.

The effectiveness of a short-term group music therapy intervention for parents who have a child with a disability

Background The relationship between positive parent-child interactions and optimal child development is well established. Families with a child with a disability may face additional challenges to establishing positive parent-child relationships. There are limited studies addressing the effectiveness of interventions which seek to address these issues with parents and young children with a disability. In particular, prior studies of music therapy with this group have been limited by small sample sizes and the use of measures of limited reliability and validity. Objective This study investigates the effectiveness of a short-term group music therapy intervention for parents who have a child with a disability and explores the factors associated with higher outcomes for participating families. Methods The participants were 201 mother-child dyads, where the child had a disability. Pre and post intervention parental questionnaires and clinician observation measures were taken on a range of parental wellbeing, parenting behaviours and child developmental factors. Descriptive data, t-tests for repeated measures and a predictive model tested via logistic regression are presented. Results Significant improvements pre to post were found for parent mental health, child communication and social skills, parenting sensitivity, parental engagement with child and acceptance of child, child responsiveness to parent, and child interest and participation in program activities. There was also evidence that parents were very satisfied with the program and that it brought social benefits to families. Reliable change on six or more indicators of parent or child functioning was predicted by attendance and parent education. Conclusions This study provides positive evidence for the effectiveness of group music therapy in promoting improved parental mental health, positive parenting and key child developmental areas. Whilst several limitations are discussed, the study does address some of the gaps in the music therapy evidence base in this area.

Definition of an airworthiness certification framework for civil unmanned aircraft systems

The development of effective safety regulations for unmanned aircraft systems (UAS) is an issue of paramount concern for industry. The development of this framework is a prerequisite for greater UAS access to civil airspace and, subsequently, the continued growth of the UAS industry. The direct use of the existing conventionally piloted aircraft (CPA) airworthiness certification framework for the regulation of UAS has a number of limitations. The objective of this paper is to present one possible approach for the structuring of airworthiness regulations for civilian UAS. The proposed approach facilitates a more systematic, objective and justifiable method for managing the spectrum of risk associated with the diversity of UAS and their potential operations. A risk matrix is used to guide the development of an airworthiness certification matrix (ACM). The ACM provides a structured categorisation that facilitates the future tailoring of regulations proportionate to the levels of risk associated with the operation of the UAS. As a result, an objective and traceable link may be established between mandated regulations and the overarching objective for an equivalent level of safety to CPA. The ACM also facilitates the systematic consideration of a range of technical and operational mitigation strategies. For these reasons, the ACM is proposed as a suitable method for the structuring of an airworthiness certification framework for civil or commercially operated UAS (i.e., the UAS equivalent in function to the Part 21 regulations for civil CPA) and for the further structuring of requirements on the operation of UAS in un-segregated airspace.