The number of light commercial vehicles (LCV) in cities is growing, which puts increasing pressure on the livability of cities. Freight vehicles are large contributors to polluting air and CO2 emissions and generate problems in terms of safety, noise and loss of public space. Small electric freight vehicles and cargo bikes can offer a solution, as they take less space, can maneuver easily and do not emit local pollution. There is an increasing interest in these vehicle, called light electric freight vehicles (LEFV’s), among logistic service providers in European cities. However, various technical and operational challenges impede large scale implementation. Within the two-year LEVV-LOGIC project, (2016-2018) the use of LEFV’s for city logistics is explored. The project combines expertise on logistics, vehicle design, charging infrastructure and business modelling to find the optimal concept in which LEFV’s can be a financial competitive alternative for conventional freight vehicles. This contribution to EVS30 will present the project’s first year results, showing the guideline for and the applied design of LEFV for future urban city logistics.
Background A variety of options and techniques for causing implicit and explicit motor learning have been described in the literature. The aim of the current paper was to provide clearer guidance for practitioners on how to apply motor learning in practice by exploring experts’ opinions and experiences, using the distinction between implicit and explicit motor learning as a conceptual departure point. Methods A survey was designed to collect and aggregate informed opinions and experiences from 40 international respondents who had demonstrable expertise related to motor learning in practice and/or research. The survey was administered through an online survey tool and addressed potential options and learning strategies for applying implicit and explicit motor learning. Responses were analysed in terms of consensus ( 70%) and trends ( 50%). A summary figure was developed to illustrate a taxonomy of the different learning strategies and options indicated by the experts in the survey.
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Background: Health care practitioners' knowledge and attitudes influence patients’ beliefs and health outcomes in musculoskeletal (MSK) pain. It is unclear to what extent physiotherapists undertaking a postgraduate master in manual therapy (MT students) possess the knowledge and attitudes toward pain neuroscience to be able to apply the biopsychosocial model in patients with MSK pain. Objectives: The aim of this study was to assess the knowledge and attitudes toward pain neuroscience in MT students. Design: A cross-sectional study. Method: Self-reported knowledge and attitudes were measured among students (n = 662) at baseline and in all years of the MT postgraduate programs in the Netherlands. The Knowledge and Attitudes of Pain questionnaire (KNAP) was used as a primary measure. Difference in KNAP-scores between baseline (0), year 1, year 2 and year 3 was tested using a one-way ANOVA (hypothesis: 0 < 1
