Optimisation of performance in top level athletes : an action-based coping approach : a commentary

INTRODUCTION In their target article, Yuri Hanin and Muza Hanina outlined a novel multidisciplinary approach to performance optimisation for sport psychologists called the Identification-Control-Correction (ICC) programme. According to the authors, this empirically-verified, psycho-pedagogical strategy is designed to improve the quality of coaching and consistency of performance in highly skilled athletes and involves a number of steps including: (i) identifying and increasing self-awareness of ‘optimal’ and ‘non-optimal’ movement patterns for individual athletes; (ii) learning to deliberately control the process of task execution; and iii), correcting habitual and random errors and managing radical changes of movement patterns. Although no specific examples were provided, the ICC programme has apparently been successful in enhancing the performance of Olympic-level athletes. In this commentary, we address what we consider to be some important issues arising from the target article. We specifically focus attention on the contentious topic of optimization in neurobiological movement systems, the role of constraints in shaping emergent movement patterns and the functional role of movement variability in producing stable performance outcomes. In our view, the target article and, indeed, the proposed ICC programme, would benefit from a dynamical systems theoretical backdrop rather than the cognitive scientific approach that appears to be advocated. Although Hanin and Hanina made reference to, and attempted to integrate, constructs typically associated with dynamical systems theoretical accounts of motor control and learning (e.g., Bernstein’s problem, movement variability, etc.), these ideas required more detailed elaboration, which we provide in this commentary.

Realistic yet humanitarian? The comprehensive plan of action and refugee policy in Southeast Asia

The 1989 Comprehensive Plan of Action (CPA) has recently been described as a successful example of how to manage large protracted refugee flows. However, this article revisits the circumstances surrounding the CPA used to resolve the prolonged Indo-Chinese refugee crisis to highlight that part of its development was linked to the fact that Southeast Asian states refused to engage with proposed solutions, which did not include repatriation for the majority of the Indo-Chinese asylum seekers who were deemed to be ‘non-genuine’1 ( UNGA, 1989a) refugees. This resulted in the CPA often forcibly repatriating ‘non-genuine’ refugees, particularly near the end of its program. This article reviews the CPA in order to assess whether its practices and results should be repeated.

The constitutional power to make war: domestic legal issues raised by Australia's action in Iraq

The legal power to declare war has traditionally been a part of a prerogative to be exercised solely on advice that passed from the King to the Governor-General no later than 1942. In 2003, the Governor- General was not involved in the decision by the Prime Minister and Cabinet to commit Australian troops to the invasion of Iraq. The authors explore the alternative legal means by which Australia can go to war - means the government in fact used in 2003 - and the constitutional basis of those means. While the prerogative power can be regulated and/or devolved by legislation, and just possibly by practice, there does not seem to be a sound legal basis to assert that the power has been devolved to any other person. It appears that in 2003 the Defence Minister used his legal powers under the Defence Act 1903 (Cth) (as amended in 1975) to give instructions to the service head(s). A powerful argument could be made that the relevant sections of the Defence Act were not intended to be used for the decision to go to war, and that such instructions are for peacetime or in bello decisions. If so, the power to make war remains within the prerogative to be exercised on advice. Interviews with the then Governor-General indicate that Prime Minister Howard had planned to take the matter to the Federal Executive Council 'for noting', but did not do so after the Governor-General sought the views of the then Attorney-General about relevant issues of international law. The exchange raises many issues, but those of interest concern the kinds of questions the Governor-General could and should ask about proposed international action and whether they in any way mirror the assurances that are uncontroversially required for domestic action. In 2003, the Governor-General's scrutiny was the only independent scrutiny available because the legality of the decision to go to war was not a matter that could be determined in the High Court, and the federal government had taken action in March 2002 that effectively prevented the matter coming before the International Court of Justice

Grounding action in visuo-haptic space using experience networks

Traditional approaches to the use of machine learning algorithms do not provide a method to learn multiple tasks in one-shot on an embodied robot. It is proposed that grounding actions within the sensory space leads to the development of action-state relationships which can be re-used despite a change in task. A novel approach called an Experience Network is developed and assessed on a real-world robot required to perform three separate tasks. After grounded representations were developed in the initial task, only minimal further learning was required to perform the second and third task.

Mapping the dynamic of Project Management field : Project Management in action

Focusing on the role within and between organizations of the project management discipline to design and implement strategy, as source of competitive advantage, leads us to question the scientific field behind this discipline. This science should be the basis for the development and use of bodies of knowledge, standards, certification programs, education, and competencies, and beyond this as a source of value for people, organizations, and society. Thus the importance to characterize, define, and understand this field and its underlying strength, basis, and development is paramount. For this purpose we propose to give some insights on the current situation. This will lead us to clarify our epistemological position and demonstrate that both constructivism and positivist approaches are required to seize the full dimension and dynamics of the field.We will referee to sociology of actor-networks and qualitative scientometrics leading to the choice of the co-word analysis method in enabling us to capture the project management field and its dynamics.Results of a study based on the analysis of ABI Inform database will be presented and some future trends and scenarios proposed.

The role of education and awareness in workplace alcohol and drug use in the Australian construction industry : proposed program of research and preliminary results

The main aim of this paper is to outline a proposed program of research which will attempt to quantify the extent of the problem of alcohol and other drugs in the Australian construction industry, and furthermore, develop an appropriate industry-wide policy and cultural change management program and implementation plan to address the problem. This paper will also present preliminary results from the study. The study will use qualitative and quantitative methods (in the form of interviews and surveys, respectively) to evaluate the extent of the problem of alcohol and other drug use in this industry, to ascertain the feasibility of an industry-wide policy and cultural change management program, and to develop an appropriate implementation plan. The study will be undertaken in several construction organisations, at selected sites in South Australia, Victoria and Northern Territory. It is anticipated that approximately 500 employees from the participating organisations across Australia will take part in the study. The World Health Organisation’s Alcohol Use Disorders Identification Test (AUDIT) will be used to measure the extent of alcohol use in the industry. Illicit drug use, ‘‘readiness to change’’, impediments to reducing impairment, feasibility of proposed interventions, and employee attitudes and knowledge regarding workplace AOD impairment, will also be measured through a combination of interviews and surveys. Among the preliminary findings, for 51% (n=127) of respondents, score on the AUDIT indicated alcohol use at hazardous levels. Of the respondents who were using alcohol at hazardous levels, 76% reported (n97) that they do not have a problem with drinking and 54% (n=68) reported that it would be easy to ‘‘cut down’’ or stop drinking. Nearly half (49%) of all respondents (n=122) had used marijuana/cannabis at some time prior to being surveyed. The use of other illicit substances was much less frequently reported. Preliminary interview findings indicated a lack of adequate employee knowledge regarding the physical effects of alcohol and other drugs in the workplace. As for conclusions, the proposed study will address a major gap in the literature with regard to the extent of the problem of alcohol and other drug use in the construction industry in Australia. The study will also develop and implement a national, evidence-based workplace policy, with the aim of mitigating the deleterious effects of alcohol and other drugs in this industry.

Spatio temporal feature evaluation for action recognition

Spatio-Temporal interest points are the most popular feature representation in the field of action recognition. A variety of methods have been proposed to detect and describe local patches in video with several techniques reporting state of the art performance for action recognition. However, the reported results are obtained under different experimental settings with different datasets, making it difficult to compare the various approaches. As a result of this, we seek to comprehensively evaluate state of the art spatio- temporal features under a common evaluation framework with popular benchmark datasets (KTH, Weizmann) and more challenging datasets such as Hollywood2. The purpose of this work is to provide guidance for researchers, when selecting features for different applications with different environmental conditions. In this work we evaluate four popular descriptors (HOG, HOF, HOG/HOF, HOG3D) using a popular bag of visual features representation, and Support Vector Machines (SVM)for classification. Moreover, we provide an in-depth analysis of local feature descriptors and optimize the codebook sizes for different datasets with different descriptors. In this paper, we demonstrate that motion based features offer better performance than those that rely solely on spatial information, while features that combine both types of data are more consistent across a variety of conditions, but typically require a larger codebook for optimal performance.

Kernel analysis on Grassmann manifolds for action recognition

Modelling video sequences by subspaces has recently shown promise for recognising human actions. Subspaces are able to accommodate the effects of various image variations and can capture the dynamic properties of actions. Subspaces form a non-Euclidean and curved Riemannian manifold known as a Grassmann manifold. Inference on manifold spaces usually is achieved by embedding the manifolds in higher dimensional Euclidean spaces. In this paper, we instead propose to embed the Grassmann manifolds into reproducing kernel Hilbert spaces and then tackle the problem of discriminant analysis on such manifolds. To achieve efficient machinery, we propose graph-based local discriminant analysis that utilises within-class and between-class similarity graphs to characterise intra-class compactness and inter-class separability, respectively. Experiments on KTH, UCF Sports, and Ballet datasets show that the proposed approach obtains marked improvements in discrimination accuracy in comparison to several state-of-the-art methods, such as the kernel version of affine hull image-set distance, tensor canonical correlation analysis, spatial-temporal words and hierarchy of discriminative space-time neighbourhood features.

Consumer product-related injuries in Queensland children : A snapshot of current problem areas for potential action

This report presents a snapshot from work which was funded by the Queensland Injury Prevention Council in 2010-11 titled “Feasibility of Using Health Data Sources to Inform Product Safety Surveillance in Queensland children”. The project provided an evaluation of the current available evidence-base for identification and surveillance of product-related injuries in children in Queensland and Australia. A comprehensive 300 page report was produced (available at: http://eprints.qut.edu.au/46518/) and a series of recommendations were made which proposed: improvements in the product safety data system, increased utilisation of health data for proactive and reactive surveillance, enhanced collaboration between the health sector and the product safety sector, and improved ability of health data to meet the needs of product safety surveillance. At the conclusion of the project, a Consumer Product Injury Research Advisory group (CPIRAG) was established as a working party to the Queensland Injury Prevention Council (QIPC), to prioritise and advance these recommendations and to work collaboratively with key stakeholders to promote the role of injury data to support product safety policy decisions at the Queensland and national level. This group continues to meet monthly and is comprised of the organisations represented on the second page of this report. One of the key priorities of the CPIRAG group for 2012 was to produce a snapshot report to highlight problem areas for potential action arising out of the larger report. Subsequent funding to write this snapshot report was provided by the Institute for Health and Biomedical Innovation, Injury Prevention and Rehabilitation Domain at QUT in 2012. This work was undertaken by Dr Kirsten McKenzie and researchers from QUT's Centre for Accident Research and Road Safety - Queensland. This snapshot report provides an evidence base for potential further action on a range of children’s products that are significantly represented in injury data. Further information regarding injury hazards, safety advice and regulatory responses are available on the Office of Fair Trading (OFT) Queensland website and the Product Safety Australia websites. Links to these resources are provided for each product reviewed.

Ginger - mechanism of action in chemotherapy-induced nausea and vomiting: A review

Despite advances in anti-emetic therapy, chemotherapy-induced nausea and vomiting (CINV) still poses a significant burden to patients undergoing chemotherapy. Nausea, in particular, is still highly prevalent in this population. Ginger has been traditionally used as a folk remedy for gastrointestinal complaints and has been suggested as a viable adjuvant treatment for nausea and vomiting in the cancer context. Substantial research has revealed ginger to possess properties that could exert multiple beneficial effects on chemotherapy patients who experience nausea and vomiting. Bioactive compounds within the rhizome of ginger, particularly the gingerol and shogaol class of compounds, interact with several pathways that are directly implicated in CINV in addition to pathways that could play secondary roles by exacerbating symptoms. These properties include 5-HT3, substance P and acetylcholine receptor antagonism; anti-inflammatory properties; and modulation of cellular redox signalling, vasopressin release, gastrointestinal motility, and gastric emptying rate. This review outlines these proposed mechanisms by discussing the results of clinical, in vitro and animal studies both within the chemotherapy context and in other relevant fields. The evidence presented in this review indicates that ginger possesses multiple properties that could be beneficial in reducing chemotherapy-induced nausea and vomiting.

Monitoring and benchmarking government policies and actions to improve the healthiness of food environments : a proposed Government Healthy Food Environment Policy Index

Government action is essential to increase the healthiness of food environments and reduce obesity, diet-related non-communicable diseases (NCDs), and their related inequalities. This paper proposes a monitoring framework to assess government policies and actions for creating healthy food environments. Recommendations from relevant authoritative organizations and expert advisory groups for reducing obesity and NCDs were examined, and pertinent components were incorporated into a comprehensive framework for monitoring government policies and actions. A Government Healthy Food Environment Policy Index (Food-EPI) was developed, which comprises a ‘policy’ component with seven domains on specific aspects of food environments, and an ‘infrastructure support’ component with seven domains to strengthen systems to prevent obesity and NCDs. These were revised through a week-long consultation process with international experts. Examples of good practice statements are proposed within each domain, and these will evolve into benchmarks established by governments at the forefront of creating and implementing food policies for good health. A rating process is proposed to assess a government's level of policy implementation towards good practice. The Food-EPI will be pre-tested and piloted in countries of varying size and income levels. The benchmarking of government policy implementation has the potential to catalyse greater action to reduce obesity and NCDs.

Multi-action recognition via stochastic modelling of optical flow and gradients

In this paper we propose a novel approach to multi-action recognition that performs joint segmentation and classification. This approach models each action using a Gaussian mixture using robust low-dimensional action features. Segmentation is achieved by performing classification on overlapping temporal windows, which are then merged to produce the final result. This approach is considerably less complicated than previous methods which use dynamic programming or computationally expensive hidden Markov models (HMMs). Initial experiments on a stitched version of the KTH dataset show that the proposed approach achieves an accuracy of 78.3%, outperforming a recent HMM-based approach which obtained 71.2%.

Putting an "end" to the motor cortex representations of action words

Language processing is an example of implicit learning of multiple statistical cues that provide probabilistic information regarding word structure and use. Much of the current debate about language embodiment is devoted to how action words are represented in the brain, with motor cortex activity evoked by these words assumed to selectively reflect conceptual content and/or its simulation. We investigated whether motor cortex activity evoked by manual action words (e.g., caress) might reflect sensitivity to probabilistic orthographic-phonological cues to grammatical category embedded within individual words. We first review neuroimaging data demonstrating that nonwords evoke activity much more reliably than action words along the entire motor strip, encompassing regions proposed to be action category specific. Using fMRI, we found that disyllabic words denoting manual actions evoked increased motor cortex activity compared with non-body-part-related words (e.g., canyon), activity which overlaps that evoked by observing and executing hand movements. This result is typically interpreted in support of language embodiment. Crucially, we also found that disyllabic nonwords containing endings with probabilistic cues predictive of verb status (e.g., -eve) evoked increased activity compared with nonwords with endings predictive of noun status (e.g., -age) in the identical motor area. Thus, motor cortex responses to action words cannot be assumed to selectively reflect conceptual content and/or its simulation. Our results clearly demonstrate motor cortex activity reflects implicit processing of ortho-phonological statistical regularities that help to distinguish a word's grammatical class.

Human action recognition from video sequences

This PhD research has proposed new machine learning techniques to improve human action recognition based on local features. Several novel video representation and classification techniques have been proposed to increase the performance with lower computational complexity. The major contributions are the construction of new feature representation techniques, based on advanced machine learning techniques such as multiple instance dictionary learning, Latent Dirichlet Allocation (LDA) and Sparse coding. A Binary-tree based classification technique was also proposed to deal with large amounts of action categories. These techniques are not only improving the classification accuracy with constrained computational resources but are also robust to challenging environmental conditions. These developed techniques can be easily extended to a wide range of video applications to provide near real-time performance.

Mechanism of action of selenious acid in the electrodeposition of manganese

The effect of selenious acid as an addition agent in the electrodeposition of manganese was studied by analysing the current-potential curves for manganese deposition. The mechanism of action of this addition agent was found to be essentially similar to that proposed for sulphur dioxide, namely to affect the manganese deposition indirectly by influencing the hydrogen evolution reaction which is a parallel reaction at the electrode surface.