Functional Imagery Training to reduce snacking: Testing a novel motivational intervention based on Elaborated Intrusion theory

Functional Imagery Training (FIT) is a new theory-based, manualized intervention that trains positive goal imagery. Multisensory episodic imagery of proximal personal goals is elicited and practised, to sustain motivation and compete with less functional cravings. This study tested the impact of a single session of FIT plus a booster phone call on snacking. In a stepped-wedge design, 45 participants who wanted to lose weight or reduce snacking were randomly assigned to receive a session of FIT immediately or after a 2-week delay. High-sugar and high-fat snacks were recorded using timeline follow back for the previous 3 days, at baseline, 2 and 4 weeks. At 2 weeks, snacking was lower in the immediate group than in the delayed group, and the reduction after FIT was replicated in the delayed group between 2 and 4 weeks. Frequencies of motivational thoughts about snack reduction rose following FIT for both groups, and this change correlated with reductions in snacking and weight loss. By showing that FIT can support change in eating behaviours, these findings show its potential as a motivational intervention for weight management.

Water management capacity building to support rapidly developing mining economies

Many developing countries are experiencing rapid expansion in mining with associated water impacts. In most cases mining expansion is outpacing the building of national capacity to ensure that sustainable water management practices are implemented. Since 2011, Australia's International Mining for Development Centre (IM4DC) has funded capacity building in such countries including a program of water projects. Five projects in particular (principally covering experiences from Peru, Colombia, Ghana, Zambia, Indonesia, Philippines and Mongolia) have provided insight into water capacity building priorities and opportunities. This paper reviews the challenges faced by water stakeholders, and proposes the associated capacity needs. The paper uses the evidence derived from the IM4DC projects to develop a set of specific capacity-building recommendations. Recommendations include: the incorporation of mine water management in engineering and environmental undergraduate courses; secondments of staff to suitable partner organisations; training to allow site staff to effectively monitor water including community impacts; leadership training to support a water stewardship culture; training of officials to support implementation of catchment management approaches; and the empowerment of communities to recognise and negotiate solutions to mine-related risks. New initiatives to fund the transfer of multi-disciplinary knowledge from nations with well-developed water management practices are called for.

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...

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.

Minimum enclosing spheres formulations for support vector ordinal regression

We present two new support vector approaches for ordinal regression. These approaches find the concentric spheres with minimum volume that contain most of the training samples. Both approaches guarantee that the radii of the spheres are properly ordered at the optimal solution. The size of the optimization problem is linear in the number of training samples. The popular SMO algorithm is adapted to solve the resulting optimization problem. Numerical experiments on some real-world data sets verify the usefulness of our approaches for data mining.

Scalable non-linear Support Vector Machine using hierarchical clustering

This paper discusses a method for scaling SVM with Gaussian kernel function to handle large data sets by using a selective sampling strategy for the training set. It employs a scalable hierarchical clustering algorithm to construct cluster indexing structures of the training data in the kernel induced feature space. These are then used for selective sampling of the training data for SVM to impart scalability to the training process. Empirical studies made on real world data sets show that the proposed strategy performs well on large data sets.

Support vector machine for evaluating seismic-liquefaction potential using shear wave velocity

The use of the shear wave velocity data as a field index for evaluating the liquefaction potential of sands is receiving increased attention because both shear wave velocity and liquefaction resistance are similarly influenced by many of the same factors such as void ratio, state of stress, stress history and geologic age. In this paper, the potential of support vector machine (SVM) based classification approach has been used to assess the liquefaction potential from actual shear wave velocity data. In this approach, an approximate implementation of a structural risk minimization (SRM) induction principle is done, which aims at minimizing a bound on the generalization error of a model rather than minimizing only the mean square error over the data set. Here SVM has been used as a classification tool to predict liquefaction potential of a soil based on shear wave velocity. The dataset consists the information of soil characteristics such as effective vertical stress (sigma'(v0)), soil type, shear wave velocity (V-s) and earthquake parameters such as peak horizontal acceleration (a(max)) and earthquake magnitude (M). Out of the available 186 datasets, 130 are considered for training and remaining 56 are used for testing the model. The study indicated that SVM can successfully model the complex relationship between seismic parameters, soil parameters and the liquefaction potential. In the model based on soil characteristics, the input parameters used are sigma'(v0), soil type. V-s, a(max) and M. In the other model based on shear wave velocity alone uses V-s, a(max) and M as input parameters. In this paper, it has been demonstrated that Vs alone can be used to predict the liquefaction potential of a soil using a support vector machine model. (C) 2010 Elsevier B.V. All rights reserved.

Knowledge Exchange RDM Training & Skills Workshop, 9-10 Feb 2016, London

In today’s changing research environment, RDM is important in all stages of research. The skills and know-how in RDM that researchers and research support staff need, should be nurtured all though their career. At the end of 2015, KE initiated a project to compare approaches in RDM training within the partnership’s five member countries. The project was structured around two strands of activity: In the last months of 2015 a survey was conducted to collect information on current practice around RDM training, in order to provide an overview of the RDM training landscape. In February 2016 a workshop was held to share successful approaches to RDM training and capacity building provided within institutions and by infrastructure. The report describes the outputs of both the analysis of the survey and the outcomes of the workshop. The document provides an evidence base and informed suggestions to help improve RDM training practices in KE partner countries and beyond.

Training workshop proceedings: adaptive co-management of fisheries (January 21-25, Boyboison Lodge, Fijai, Ghana)

The Adaptive Collaborative Management of Fisheries Training workshop was held in Sekondi, Western Region of Ghana as part of the project “Integrated Coastal and Fisheries Governance Initiative” locally referred to as “H n Mpoano”. The aim of the project is to support the government of Ghana achieve its development objective of poverty reduction, food security, sustainable fisheries management and biodiversity conservation and contributes to its vision: Ghana’s coastal and marine ecosystems are sustainably managed to provide goods and services that generate long-term socioeconomic benefit to communities while sustaining biodiversity.

Institutional support for freshwater aquaculture development: a study of Mirzapur district of Uttar Pradesh, India

The aquaculture sector has been playing an increasingly dominating role in Indian fisheries scenario since the last two and half decades. Introduction of induced breeding and composite fish culture (CFC) technologies has changed the freshwater aquaculture sector in India. Institutional support has been one of the most crucial aspects in all fisheries development programs, more so in the Indian context where most of fish farmers are socially and economically weak. The innovation of CFC technology in freshwater aquaculture sector in the early seventies generated the need for adequate and effective institutional support to farmers. Under the freshwater aquaculture development program, the Fish Farmers Development Agencies (FFDA) have been established at district level to provide technical and extension support to the farming community besides arranging ponds on lease and supply of seeds. In addition to above, FFDAs are also expected to arrange loans from banks and provide subsidies. Thus, FFDAs are meant to provide institutional support to fish farming community in the country. In view of the above, an effort was made to study the adequacy and effectiveness of institutional support provided by the FFDA, Mirzapur for the development of aquaculture in Mirzapur district of Uttar Pradesh {U.P.), India. Study reveals that leasing of ponds for fish farming has been favourable to economically weaker sections of societies while bank loan accessibility is more for those having relatively higher economic status. Though the FFDA, Mirzapur performed well in providing training to potential fish farmers and creating awareness about fish farming, its effectiveness could not be equally seen in seed supply.

Extending noise robust structured support vector machines to larger vocabulary tasks

This paper describes a structured SVM framework suitable for noise-robust medium/large vocabulary speech recognition. Several theoretical and practical extensions to previous work on small vocabulary tasks are detailed. The joint feature space based on word models is extended to allow context-dependent triphone models to be used. By interpreting the structured SVM as a large margin log-linear model, illustrates that there is an implicit assumption that the prior of the discriminative parameter is a zero mean Gaussian. However, depending on the definition of likelihood feature space, a non-zero prior may be more appropriate. A general Gaussian prior is incorporated into the large margin training criterion in a form that allows the cutting plan algorithm to be directly applied. To further speed up the training process, 1-slack algorithm, caching competing hypothesis and parallelization strategies are also proposed. The performance of structured SVMs is evaluated on noise corrupted medium vocabulary speech recognition task: AURORA 4. © 2011 IEEE.

Training needs analysis of healthcare library staff, undertaken for South Yorkshire Workforce Development Confederation

Urquhart, C., Durbin, J. & Spink, S. (2004). Training needs analysis of healthcare library staff, undertaken for South Yorkshire Workforce Development Confederation. Aberystwyth: Department of Information Studies, University of Wales Aberystwyth. Sponsorship: South Yorkshire WDC (NHS)

Evaluation of resources to support production of high quality health information for patients and the public. Final report for NHS Research Outputs Programme

Durbin, J., Urquhart, C. & Yeoman, A. (2003). Evaluation of resources to support production of high quality health information for patients and the public. Final report for NHS Research Outputs Programme. Aberystwyth: Department of Information Studies, University of Wales Aberystwyth. Sponsorship: Department of Health

Assessing training and professional development needs of library staff. Report for National Library of Health

Urquhart, C., Spink, S. & Thomas, R., Assessing training and professional development needs of library staff. Report for National Library of Health. (2005). Aberystwyth: Department of Information Studies, University of Wales Aberystwyth Sponsorship: National Library for Health (NHS Information Authority)

Learning from triads: training undergraduates in counselling skills

Background: Research has shown that counselling skills training in undergraduate programmes is effective. However, there is potential that premature intimacy and disclosures during triad work may impact on relationships which must be maintained out-with the counselling component of the course. Little research has examined individual pedagogical practices within training. Aim: The aim of this research was to explore the experience of the practical skills training component of a counselling course for a cohort of undergraduate students, and the impact of this learning experience. The objective being an evaluation of the use of this approach for this group and of the impact of personal sharing within cohorts of undergraduates. Method: Semi-structured interviews focusing on the experience of skills training and self-disclosure during training were carried out on 12 undergraduates taking counselling skills modules as part of their BSc Psychology and Counselling degree. Thematic analysis was carried out on the interview transcripts. Results: As a result of engagement in skills training and acting as ‘clients’ for one another, individuals perceived the formation of a positive group identity with implicit ‘rules’, but also an impact of training on relationships within the group which relied on the ability to maintain boundaries and personal identities with peers, and this influenced the learning experience. The ability to manage their engagement on the programme was dependent on ongoing support and guidance from tutors. Discussion: While this pedagogical approach appears appropriate for facilitating learning and potentially provides a rich learning journey for undergraduate students, tutors must act proactively to ensure a safe learning environment.