ObjectivesTo model food group consumption and price of diet associated with achieving UK dietary recommendations while deviating as little as possible from the current UK diet, in order to support the redevelopment of the UK food-based dietary guidelines (now called the Eatwell Guide).DesignOptimisation modelling, minimising an objective function of the difference between population mean modelled and current consumption of 125 food groups, and constraints of nutrient and food-based recommendations.SettingThe UK.PopulationAdults aged 19 years and above from the National Diet and Nutrition Survey 2008–2011.Main outcome measuresProportion of diet consisting of major foods groups and price of the optimised diet.ResultsThe optimised diet has an increase in consumption of ‘potatoes, bread, rice, pasta and other starchy carbohydrates’ (+69%) and ‘fruit and vegetables’ (+54%) and reductions in consumption of ‘beans, pulses, fish, eggs, meat and other proteins’ (−24%), ‘dairy and alternatives’ (−21%) and ‘foods high in fat and sugar’ (−53%). Results within food groups show considerable variety (eg, +90% for beans and pulses, −78% for red meat). The modelled diet would cost £5.99 (£5.93 to £6.05) per adult per day, very similar to the cost of the current diet: £6.02 (£5.96 to £6.08). The optimised diet would result in increased consumption of n-3 fatty acids and most micronutrients (including iron and folate), but decreased consumption of zinc and small decreases in consumption of calcium and riboflavin.ConclusionsTo achieve the UK dietary recommendations would require large changes in the average diet of UK adults, including in food groups where current average consumption is well within the recommended range (eg, processed meat) or where there are no current recommendations (eg, dairy). These large changes in the diet will not lead to significant changes in the price of the diet.

Cognitive load theory assumes that effective instructional design is subject to the mechanisms that underpin our cognitive architecture and that understanding is constrained by the processing capacity of a limited working memory. This thesis reports the results of six experiments that applied the principles of cognitive load theory to the investigation of instructional design in music. Across the six experiments conditions differed by modality (uni or dual) and/or the nature of presentation (integrated or adjacent; simultaneous or successive). In addition, instructional formats were comprised of either two or three sources of information (text, auditory musical excerpts, musical notation). Participants were academically able Year 7 students with some previous musical experience. Following instructional interventions, students were tested using auditory and/or written problems; in addition, subjective ratings and efficiency measures were used as indicators of mental load. Together, Experiments 1 and 2 demonstrated the benefits of both dual-modal (dual-modality effect) and physically integrated formats over the same materials presented as adjacent and discrete information sources (split-attention effect), confirming the application of established cognitive load effects within the domain of music. Experiment 3 compared uni-modal formats, consisting of auditory rather than visual materials, with their dual-modal counterparts. Although some evidence for a modality effect was associated with simultaneous presentations, the uni-modal format was clearly superior when the same materials were delivered successively. Experiment 4 compared three cognitively efficient instructional formats in which either two or three information sources were

Box delivery is a complicated task and it is challenging to predict the box delivery motion associated with the box weight, delivering speed, and location. This paper presents a single task-based inverse dynamics optimization method for determining the planar symmetric optimal box delivery motion (multi-task jobs). The design variables are cubic B-spline control points of joint angle profiles. The objective function is dynamic effort, i.e., the time integral of the square of all normalized joint torques. The optimization problem includes various constraints. Joint angle profiles are validated through experimental results using root-mean-square-error (RMSE) and Pearson’s correlation coefficient. This research provides a practical guidance to prevent injury risks in joint torque space for workers who lift and deliver heavy objects in their daily jobs.

Box delivery is a complicated manual material handling task which needs to consider the box weight, delivering speed, stability, and location. This paper presents a subtask-based inverse dynamic optimization formulation for determining the two-dimensional (2D) symmetric optimal box delivery motion. For the subtask-based formulation, the delivery task is divided into five subtasks: lifting, the first transition step, carrying, the second transition step, and unloading. To render a complete delivering task, each subtask is formulated as a separate optimization problem with appropriate boundary conditions. For carrying and lifting subtasks, the cost function is the sum of joint torque squared. In contrast, for transition subtasks, the cost function is the combination of joint discomfort and joint torque squared. Joint angle profiles are validated through experimental results using Pearson’s correlation coefficient (r) and root-mean-square-error (RMSE). Results show that the subtask-based approach is computationally efficient for complex box delivery motion simulation. This research outcome provides a practical guidance to prevent injury risks in joint torque space for workers who deliver heavy objects in their daily jobs.