Development of a multi-dimensional measure of resilience in adolescents : the adolescent resilience questionnaire

Background: The concept of resilience has captured the imagination of researchers and policy makers over the past two decades. However, despite the ever growing body of resilience research, there is a paucity of relevant, comprehensive measurement tools. In this article, the development of a theoretically based, comprehensive multidimensional measure of resilience in adolescents is described.

Methods: Extensive literature review and focus groups with young people living with chronic illness informed the conceptual development of scales and items. Two sequential rounds of factor and scale analyses were undertaken to revise the conceptually developed scales using data collected from young people living with a chronic illness and a general population sample.

Results: The revised Adolescent Resilience Questionnaire comprises 93 items and 12 scales measuring resilience factors in the domains of self, family, peer, school and community. All scales have acceptable alpha coefficients. Revised scales closely reflect conceptually developed scales.

Conclusions: It is proposed that, with further psychometric testing, this new measure of resilience will provide researchers and clinicians with a comprehensive and developmentally appropriate instrument to measure a young person’s capacity to achieve positive outcomes despite life stressors.

Practical amine functionalization of multi-walled carbon nanotubes for effective interfacial bonding

 Improved methods of functionalizing the surfaces of multi-walled carbon nanotubes (MWCNTs) have been investigated. It is shown that a level of primary amines of 2.3%, higher than previously reported for any nitrogen-containing gas plasma treatment, can be achieved using a mixture of N2 and H2, which is preferable to using NH3. Even higher levels (3.5%) of primary amines can be achieved by coating the MWCNTs with a thin layer of plasma polymerized heptylamine. In both cases, the highest levels were achieved using a combined continuous plus pulsed plasma mode which was superior to either continuous wave or pulsed wave alone. The integrity of the MWCNT structure is maintained by the plasma treatments, and the functionalized surface improves the dispersion of the MWCNTs and their interfacial bonding with epoxy, giving superior nanoindentation performance of the composites.

A non-linear programming-based similarity reasoning scheme for modelling of monotonicity-preserving multi-input fuzzy inference systems

In this paper, the zero-order Sugeno Fuzzy Inference System (FIS) that preserves the monotonicity property is studied. The sufficient conditions for the zero-order Sugeno FIS model to satisfy the monotonicity property are exploited as a set of useful governing equations to facilitate the FIS modelling process. The sufficient conditions suggest a fuzzy partition (at the rule antecedent part) and a monotonically-ordered rule base (at the rule consequent part) that can preserve the monotonicity property. The investigation focuses on the use of two Similarity Reasoning (SR)-based methods, i.e., Analogical Reasoning (AR) and Fuzzy Rule Interpolation (FRI), to deduce each conclusion separately. It is shown that AR and FRI may not be a direct solution to modelling of a multi-input FIS model that fulfils the monotonicity property, owing to the difficulty in getting a set of monotonically-ordered conclusions. As such, a Non-Linear Programming (NLP)-based SR scheme for constructing a monotonicity-preserving multi-input FIS model is proposed. In the proposed scheme, AR or FRI is first used to predict the rule conclusion of each observation. Then, a search algorithm is adopted to look for a set of consequents with minimized root means square errors as compared with the predicted conclusions. A constraint imposed by the sufficient conditions is also included in the search process. Applicability of the proposed scheme to undertaking fuzzy Failure Mode and Effect Analysis (FMEA) tasks is demonstrated. The results indicate that the proposed NLP-based SR scheme is useful for preserving the monotonicity property for building a multi-input FIS model with an incomplete rule base.

An evolutionary-based similarity reasoning scheme for monotonic multi-input fuzzy inference systems

In this paper, an Evolutionary-based Similarity Reasoning (ESR) scheme for preserving the monotonicity property of the multi-input Fuzzy Inference System (FIS) is proposed. Similarity reasoning (SR) is a useful solution for undertaking the incomplete rule base problem in FIS modeling. However, SR may not be a direct solution to designing monotonic multi-input FIS models, owing to the difficulty in getting a set of monotonically-ordered conclusions. The proposed ESR scheme, which is a synthesis of evolutionary computing, sufficient conditions, and SR, provides a useful solution to modeling and preserving the monotonicity property of multi-input FIS models. A case study on Failure Mode and Effect Analysis (FMEA) is used to demonstrate the effectiveness of the proposed ESR scheme in undertaking real world problems that require the monotonicity property of FIS models.

The potential for measuring ethnicity and health in a multicultural milieu - the case of type 2 diabetes in Australia

Objective
Ethnicity influences health in many ways. For example, type 2 diabetes (T2DM) is disproportionately prevalent among certain ethnic groups. Assessing ethnicity is difficult, and numerous proxy measures are used to capture its various components. Australian guidelines specify a set of variables for measuring ethnicity, and how such parameters should be categorised. Using T2DM data collections as an illustrative example, this study sought to examine how ethnicity is measured in Australian health databases and, by comparing current practice with Australia’s existing benchmark recommendations, to identify potential areas for improvement of the health data landscape.

The design and implementation of a novel method for quantifying training loads in elite rowing: the T2minute method

Introduction: A systematic approach to managing the training of elite athletes is supported by accurate training load measurement. However, quantifying the training of elite Australian rowers is complex due to unique challenges: 1) the multi-centre, multi-state structure of the national program; 2) the variety of training undertaken, incorporating rowing-specific and non-specific modalities, with continuous and interval efforts that span the full intensity spectrum; and 3) the limitations of existing quantification methods for capturing total training loads undertaken from varied training. These challenges highlighted a need to create a consistent, location-independent framework for prescribing training in elite rowing, with a capacity to account for varied training. Methods: An in-house proprietary measure (the T2minute method) was developed at the National Rowing Centre of Excellence (NRCE), as a collaborative project between sport scientists and national squad coaches. The design phase was informed by assessments of the existing training measures, and built upon standardised intensity zones established at the Australian Institute of Sport. A common measurement unit was chosen: one T2minute equates to one minute of on-water single scull rowing at T2 intensity (∼60–72% VO2max). Each intensity zone was assigned a weighting factor according to the curvilinear relationship between power output, intensity, and blood lactate response. Each training mode was assigned a weighting factor based on whether coaches perceived it to be “harder” or “easier” than onwater rowing. With coaches’ feedback, the method was refined over a period of five months. The T2minute method was implemented as the core framework for prescribing training for elite Australian rowers throughout the 2009–2012 Olympic cycle. Results: The implementation of the T2minute method successfully established consistency with training prescription and monitoring practices within the NRCE high performance program. The national roll out this method has influenced rowing training methodology at elite and sub-elite levels in Australia. Since implementation, the method has undergone scientific validation. Further research is underway, utilising the method to explore complex relationships between rowers’ training and performance outcomes. Conclusion: The T2minute method is a novel approach that allows rowing coaches and sport scientists to utilise one consistent system to quantify load from varied training. Its implementation represents a considerable achievement in establishing a common framework for managing the training process within a complex organisational structure. This collaborative approach used to develop the T2minute method provides unique insight into the important considerations and practical challenges of applying training science to enhance elite sport performance.

(1)H-NMR analysis of the human urinary metabolome in response to an 18-month multi-component exercise program and calcium-vitamin-D3 supplementation in older men

The musculoskeletal benefits of calcium and vitamin-D3 supplementation and exercise have been extensively studied, but the effect on metabolism remains contentious. Urine samples were analyzed by (1)H-NMR spectroscopy from participants recruited for an 18-month, randomized controlled trial of a multi-component exercise program and calcium and vitamin-D3 fortified milk consumption. It was shown previously that no increase in musculoskeletal composition was observed for participants assigned to the calcium and vitamin-D3 intervention, but exercise resulted in increased bone mineral density, total lean body mass, and muscle strength. Retrospective metabolomics analysis of urine samples from patients involved in this study revealed no distinct changes in the urinary metabolome in response to the calcium and vitamin-D3 intervention, but significant changes followed the exercise intervention, notably a reduction in creatinine and an increase in choline, guanidinoacetate, and hypoxanthine (p < 0.001, fold change > 1.5). These metabolites are intrinsically involved in anaerobic ATP synthesis, intracellular buffering, and methyl-balance regulation. The exercise intervention had a marked effect on the urine metabolome and markers of muscle turnover but none of these metabolites were obvious markers of bone turnover. Measurement of specific urinary exercise biomarkers may provide a basis for monitoring performance and metabolic response to exercise regimes.

A general pose estimation algorithm in a multi-Kinect system

 Microsoft Kinect which has been primarily aimed at the computer gaming industry has been used in bio-kinematic research related implementations. A multi-Kinect system can be useful in exploiting spatial diversity to increase measurement accuracy. One of the main problems in deploying multi-Kinect systems is to estimate the pose, including the position and orientation of each Kinect. In this paper, a singular value decomposition (SVD) least-squares algorithm is extended to a more generic time-series based approach to solve this pose estimation problem utilising 3D positions of one or more joints in skeletons obtained from a multi-Kinect system. Additionally, computer simulations are performed to demonstrate the use and to evaluate the efficiency of the proposed algorithm. The former is further validated with a commercial Vicon system.

Reliability and validity of the Alberta context tool (ACT) with professional nurses: Findings from a multi-study analysis

Although organizational context is central to evidence-based practice, underdeveloped measurement hindersitsassessment. The Alberta Context Tool, comprised of 59 items that tap10 modifiable contextual concepts, was developed to address this gap. The purpose of this study to examine the reliability and validity of scores obtained when the Alberta Context Tool is completed by professional nurses across different healthcare settings. Five separate studies (N = 2361 nurses across different care settings) comprised the study sample. Reliability and validity were assessed. Cronbach's alpha exceeded 0.70 for9/10 Alberta Context Tool concepts. Item-total correlations exceeded acceptable standards for 56/59items. Confirmatory Factor Analysescoordinated acceptably with the Alberta Context Tool's proposed latent structure. The mean values for each Alberta Context Tool concept increased from low to high levels of research utilization(as hypothesized) further supporting its validity. This study provides robust evidence forreliability and validity of scores obtained with the Alberta Context Tool when administered to professional nurses.

Adaptive fuzzy multi-surface sliding control of multiple-input and multiple-output autonomous flight systems

In this study, we proposed an adaptive fuzzy multi-surface sliding control (AFMSSC) for trajectory tracking of 6 degrees of freedom inertia coupled aerial vehicles with multiple inputs and multiple outputs (MIMO). It is shown that an adaptive fuzzy logic-based function approximator can be used to estimate the system uncertainties and an iterative multi-surface sliding control design can be carried out to control flight. Using AFMSSC on MIMO autonomous flight systems creates confluent control that can account for both matched and mismatched uncertainties, system disturbances and excitation in internal dynamics. It is proved that the AFMSSC system guarantees asymptotic output tracking and ultimate uniform boundedness of the tracking error. Simulation results are presented to validate the analysis.

Minimal unknown-input functional observers for multi-input multi-output LTI systems

Designing minimum possible order (minimal) disturbance-decoupled proper functional observers for multi-input multi-output (MIMO) linear time-invariant (LTI) systems is studied. It is not necessary that a minimum-order unknown-input functional observer (UIFO) exists in our proposed design procedure. If the minimum-order observer cannot be attained, the observer's order is increased sequentially through a recursive algorithm, so that the minimal order UIFO can be obtained. To the best of our knowledge, this is the first time that this specific problem is addressed. It is assumed that the system is unknown-input functional detectable, which is the least requirement for the existence of a stable UIFO. This condition also is a certificate for the convergence of our observer's order-increase algorithm. Two methodologies are demonstrated to solve the observer design equations. The second presented scheme, is a new design method that based on our observations has a better numerical performance than the first conventional one. Numerical examples and simulation results in the MATLAB/Simulink environment describe the overall observer design procedure, and highlight the efficacy of our new methodology to solve the observer equations in comparison to the conventional one.