The pulling power of chocolate: Effects of approach-avoidance training on approach bias and consumption

Previous research has shown that action tendencies to approach alcohol may be modified using computerized ApproacheAvoidance Task (AAT), and that this impacted on subsequent consumption. A recent paper in this journal (Becker, Jostman, Wiers, & Holland, 2015) failed to show significant training effects for food in three studies: Nor did it find effects on subsequent consumption. However, avoidance training to high calorie foods was tested against a control rather than Approach training. The present study used a more comparable paradigm to the alcohol studies. It randomly assigned 90 participants to ‘approach’ or ‘avoid’ chocolate images on the AAT, and then asked them to taste and rate chocolates. A significant interaction of condition and time showed that training to avoid chocolate resulted in faster avoidance responses to chocolate images, compared with training to approach it. Consistent with Becker et al.'s Study 3, no effect was found on amounts of chocolate consumed, although a newly published study in this journal (Schumacher, Kemps, & Tiggemann, 2016) did do so. The collective evidence does not as yet provide solid basis for the application of AAT training to reduction of problematic food consumption, although clinical trials have yet to be conducted.

Digital competence and professional development of vocational education and training teachers in Queensland

Teaching with digital technologies is essential to the development of 21st century students’ graduate capabilities. However, relatively little is known about the extent to which Queensland VET teachers engage with digitally-enhanced teaching, or have the capacity to do so. Using a mixed methods approach, this thesis investigated the current digital teaching capacities of VET teachers and how current professional development opportunities are helping to address their learning needs.

In-training assessment - Its potential in enhancing clinical teaching

Context In-training assessment (ITA) has established its place alongside formative and summative assessment at both the undergraduate and postgraduate level. In this paper the authors aimed to identify those characteristics of ITA that could enhance clinical teaching. Methods A literature review and discussions by an expert working group at the Ninth Cambridge Conference identified the aspects of ITA that could enhance clinical teaching. Results The features of ITA identified included defining the specific benefits to the learner, teacher and institution, and highlighting the patient as the context for ITA and clinical teaching. The ‘mapping’ of a learner’s progress towards the clinical teaching objectives by using multiple assessments over time, by multiple observers in both a systematic and opportunistic way correlates with the incremental nature of reaching clinical competence. Conclusions The importance of ITA based on both direct and indirect evidence of what the learner actually does in the real clinical setting is emphasized. Particular attention is given to addressing concerns in the more controversial areas of assessor training, ratings and documentation for ITA. Areas for future research are also identified.

Stability Training and Measurement System for Sportsperson (P84)

Balance and stability are very important for everybody and especially for sports-person who undergo extreme physical activities. Balance and stability exercises not only have a great impact on the performance of the sportsperson but also play a pivotal role in their rehabilitation. Therefore, it is very essential to have knowledge about a sportsperson’s balance and also to quantify the same. In this work, we propose a system consisting of a wobble board, with a gyro enhanced orientation sensor and a motion display for visual feedback to help the sportsperson improve their stability. The display unit gives in real time the orientation of the wobble board, which can help the sportsperson to apply necessary corrective forces to maintain neutral position. The system is compact and portable. We also quantify balance and stability using power spectral density. The sportsperson is made stand on the wobble board and the angular orientation of the wobble board is recorded for each 0.1 second interval. The signal is analized using discrete Fourier transforms. The power of this signal is related to the stability of the subject. This procedure is used to measure the balance and stability of an elite cricket team. Representative results are shown below: Table 1 represents power comparison of two subjects and Table 2 represents power comparison of left leg and right leg of one subject. This procedure can also be used in clinical practice to monitor improvement in stability dysfunction of sportsperson with injuries or other related problems undergoing rehabilitation.

12-weeks supervised exercise training is a feasible and efficacious treatment for reducing depression in youth with major depressive disorder

Introduction: Major Depressive Disorder (MDD) has high prevalence among adolescents and young adults. Evidence of any effective treatments is limited. Exercise as an effective treatment for adults has some support but studies in younger populations are lacking. Therefore the aim of this study was to investigate the feasibility and preliminary efficacy of brief motivational interviewing (MI) plus 12-weeks exercise training as a treatment for MDD in youth...

Guided respiration mindfulness therapy: Development and evaluation of a brief therapist training program

The present paper describes the development and evaluation of a standardized multi-component therapist training program in guided respiration mindfulness therapy (GRMT). GMRT is a manual-based, experimental clinical intervention involving concentrated focus on sustained self-regulation of breathing, application of mindfulness to emergent somatic experience and relaxation. Therapists (n = 61) new to the approach attended a 2-day experiential workshop and were evaluated pre-post workshop for change in intervention knowledge, as well as change in mindfulness. These trainees also participated in post-workshop focus group sessions to explore perception of the intervention. A subset of 40 therapists participated in a second training component, and 14 of these were rated for competent delivery of the intervention during participation in a clinical trial. During training, therapists personally received the treatment giving the opportunity to assess treatment session (n = 283) impact on sense of wellbeing. Results indicated a brief focused training program can equip therapists with basic knowledge and skills required to deliver the standardized manual-based treatment. Qualitative analysis of focus group sessions showed that therapists endorsed the intervention for clinical use and found it personally beneficial. This research provides a foundation for further evaluation of clinical effectiveness of the intervention.

Workplace training and generic and technical skill development in the Australian construction industry

- Purpose The purpose of this paper is to investigate the current skills gap in both generic and skill areas within the construction industry in Queensland, Australia. - Design/methodology/approach An internet-based survey was administered to collect the opinions of construction employees about the workplace-training environment and their perceptions towards training. The survey intended to address the following research questions, specifically in relation to the construction industry. - Findings The survey results reveal that whilst overall participation in workplace training is high, the current workplace training environments do not foster balanced skill development. The study reveals that in the current absence of a formal and well-balanced training mechanism, construction workers generally resort to their own informal self-development initiatives to develop the needed role-specific theoretical knowledge. - Research limitations/implications The findings of the research are based on the data primarily collected in the construction industry in Queensland, Australia. The data are limited to a single Tier 2 construction company. - Practical implications The findings of this study can be utilised to suggest improvements in the current (or develop new) workplace training initiatives. - Social implications The research suggests that workplace training has positive relationship with career growth. The results suggest that in the construction industry, employees are generally well aware of the importance of workplace training in their career development and they largely appreciate training as being a critical factor for developing their capacity to perform their roles successfully, and to maintain their employability. - Originality/value This paper is unique as it investigates the current skills gap in both generic and skill areas within the construction industry in Queensland, Australia. So far no work has been undertaken to identify and discusses the main method of workplace learning within the Tier 2 industry in the context of Queensland Australia.

Training for reduction of design waste

Construction and demolition (C&D) waste have negative impacts on the environment. As a significant proportion of C&D waste is related to the design stage of a project, there is an opportunity for architects to reduce the waste. However, research suggests that many architects often do not understand the impact of their design on waste generation. Training and education are proposed by current researchers to improve architects’ knowledge; however, this has not been adequately validated as a viable approach to solving waste issues. This research investigates architects’ perceptions towards waste management in the design phase, and determines whether they feel they are adequately skilled in reducing C&D waste. Questionnaire surveys were distributed to architects from 98 architectural firms and 25 completed surveys were returned. The results show that while architects are aware of the relationship between design and waste, ‘extra time’ and ‘lack of knowledge’ are the key barriers to implementing waste reduction strategies. In addition, the majority of respondents acknowledge their lack of skill to reduce waste through design evaluation. Therefore, training programmes can be a viable strategy to enable them to address the pressing issue of C&D waste reduction.

Mixed pixel analysis and assessment for flood mapping

The most difficult operation in flood inundation mapping using optical flood images is to map the ‘wet’ areas where trees and houses are partly covered by water. This can be referred to as a typical problem of the presence of mixed pixels in the images. A number of automatic information extracting image classification algorithms have been developed over the years for flood mapping using optical remote sensing images, with most labelling a pixel as a particular class. However, they often fail to generate reliable flood inundation mapping because of the presence of mixed pixels in the images. To solve this problem, spectral unmixing methods have been developed. In this thesis, methods for selecting endmembers and the method to model the primary classes for unmixing, the two most important issues in spectral unmixing, are investigated. We conduct comparative studies of three typical spectral unmixing algorithms, Partial Constrained Linear Spectral unmixing, Multiple Endmember Selection Mixture Analysis and spectral unmixing using the Extended Support Vector Machine method. They are analysed and assessed by error analysis in flood mapping using MODIS, Landsat and World View-2 images. The Conventional Root Mean Square Error Assessment is applied to obtain errors for estimated fractions of each primary class. Moreover, a newly developed Fuzzy Error Matrix is used to obtain a clear picture of error distributions at the pixel level. This thesis shows that the Extended Support Vector Machine method is able to provide a more reliable estimation of fractional abundances and allows the use of a complete set of training samples to model a defined pure class. Furthermore, it can be applied to analysis of both pure and mixed pixels to provide integrated hard-soft classification results. Our research also identifies and explores a serious drawback in relation to endmember selections in current spectral unmixing methods which apply fixed sets of endmember classes or pure classes for mixture analysis of every pixel in an entire image. However, as it is not accurate to assume that every pixel in an image must contain all endmember classes, these methods usually cause an over-estimation of the fractional abundances in a particular pixel. In this thesis, a subset of adaptive endmembers in every pixel is derived using the proposed methods to form an endmember index matrix. The experimental results show that using the pixel-dependent endmembers in unmixing significantly improves performance.

Explorations in the distributional and semantic similarity of words

A straightforward computation of the list of the words (the `tail words' of the list) that are distributionally most similar to a given word (the `head word' of the list) leads to the question: How semantically similar to the head word are the tail words; that is: how similar are their meanings to its meaning? And can we do better? The experiment was done on nearly 18,000 most frequent nouns in a Finnish newsgroup corpus. These nouns are considered to be distributionally similar to the extent that they occur in the same direct dependency relations with the same nouns, adjectives and verbs. The extent of the similarity of their computational representations is quantified with the information radius. The semantic classification of head-tail pairs is intuitive; some tail words seem to be semantically similar to the head word, some do not. Each such pair is also associated with a number of further distributional variables. Individually, their overlap for the semantic classes is large, but the trained classification-tree models have some success in using combinations to predict the semantic class. The training data consists of a random sample of 400 head-tail pairs with the tail word ranked among the 20 distributionally most similar to the head word, excluding names. The models are then tested on a random sample of another 100 such pairs. The best success rates range from 70% to 92% of the test pairs, where a success means that the model predicted my intuitive semantic class of the pair. This seems somewhat promising when distributional similarity is used to capture semantically similar words. This analysis also includes a general discussion of several different similarity formulas, arranged in three groups: those that apply to sets with graded membership, those that apply to the members of a vector space, and those that apply to probability mass functions.

Improved k-t BLAST for fast fMR imaging

A popular dynamic imaging technique, k-t BLAST (ktB) is studied here for BAR imaging. ktB utilizes correlations in k-space and time, to reconstruct the image time series with only a fraction of the data. The algorithm works by unwrapping the aliased Fourier conjugate space of k-t (y-f-space). The unwrapping process utilizes the estimate of the true y-f-space, by acquiring densely sampled low k-space data. The drawbacks of this method include separate training scan, blurred training estimates and aliased phase maps. The proposed changes are incorporation of phase information from the training map and using generalized-series-extrapolated training map. The proposed technique is compared with ktB on real fMRI data. The proposed changes allow for ktB to operate at an acceleration factor of 6. Performance is evaluated by comparing activation maps obtained using reconstructed images. An improvement of up to 10 dB is observed in thePSNR of activation maps. Besides, a 10% reduction in RMSE is obtained over the entire time series of fMRI images. Peak improvement of the proposed method over ktB is 35%, averaged over five data sets. (C)2010 Elsevier Inc. All rights reserved.

Comparison of Multiclass SVM Classification Methods to Use in a Supportive System for Distance Relay Coordination

This paper aims at evaluating the methods of multiclass support vector machines (SVMs) for effective use in distance relay coordination. Also, it describes a strategy of supportive systems to aid the conventional protection philosophy in combating situations where protection systems have maloperated and/or information is missing and provide selective and secure coordinations. SVMs have considerable potential as zone classifiers of distance relay coordination. This typically requires a multiclass SVM classifier to effectively analyze/build the underlying concept between reach of different zones and the apparent impedance trajectory during fault. Several methods have been proposed for multiclass classification where typically several binary SVM classifiers are combined together. Some authors have extended binary SVM classification to one-step single optimization operation considering all classes at once. In this paper, one-step multiclass classification, one-against-all, and one-against-one multiclass methods are compared for their performance with respect to accuracy, number of iterations, number of support vectors, training, and testing time. The performance analysis of these three methods is presented on three data sets belonging to training and testing patterns of three supportive systems for a region and part of a network, which is an equivalent 526-bus system of the practical Indian Western grid.