Rethinking ‘Rational Imitation’ in 14-Month-Old Infants: A Perceptual Distraction Approach

In their widely noticed study, Gergely, Bekkering, and Király (2002) showed that 14-month-old infants imitated an unusual action only if the model freely chose to perform this action and not if the choice of the action could be ascribed to external constraints. They attributed this kind of selective imitation to the infants' capacity of understanding the principle of rational action. In the current paper, we present evidence that a simpler approach of perceptual distraction may be more appropriate to explain their results. When we manipulated the saliency of context stimuli in the two original conditions, the results were exactly opposite to what rational imitation predicts. Based on these findings, we reject the claim that the notion of rational action plays a key role in selective imitation in 14-month-olds

Democratic population decisions result in robust policy-gradient learning: A parametric study with GPU simulations

High performance computing on the Graphics Processing Unit (GPU) is an emerging field driven by the promise of high computational power at a low cost. However, GPU programming is a non-trivial task and moreover architectural limitations raise the question of whether investing effort in this direction may be worthwhile. In this work, we use GPU programming to simulate a two-layer network of Integrate-and-Fire neurons with varying degrees of recurrent connectivity and investigate its ability to learn a simplified navigation task using a policy-gradient learning rule stemming from Reinforcement Learning. The purpose of this paper is twofold. First, we want to support the use of GPUs in the field of Computational Neuroscience. Second, using GPU computing power, we investigate the conditions under which the said architecture and learning rule demonstrate best performance. Our work indicates that networks featuring strong Mexican-Hat-shaped recurrent connections in the top layer, where decision making is governed by the formation of a stable activity bump in the neural population (a "non-democratic" mechanism), achieve mediocre learning results at best. In absence of recurrent connections, where all neurons "vote" independently ("democratic") for a decision via population vector readout, the task is generally learned better and more robustly. Our study would have been extremely difficult on a desktop computer without the use of GPU programming. We present the routines developed for this purpose and show that a speed improvement of 5x up to 42x is provided versus optimised Python code. The higher speed is achieved when we exploit the parallelism of the GPU in the search of learning parameters. This suggests that efficient GPU programming can significantly reduce the time needed for simulating networks of spiking neurons, particularly when multiple parameter configurations are investigated. © 2011 Richmond et al

University–industry collaboration: using meta-rules to overcome barriers to knowledge transfer

This is the final version of the article. Available from Springer Verlag via the DOI in this record.University–industry knowledge transfer is an important source wealth of creation for all partners; however, the practical management of this activity within universities is often hampered by procedural rigidity either through the absence of decision-making protocols to reconcile conflicting priorities or through the inconsistent implementation of existing policies. This is problematic, since it can impede operational effectiveness, prevent inter-organisational knowledge-creation and hamper organisational learning. This paper addresses this issue by adopting a cross-discipline approach and presenting meta-rules as a solution to aid organisational decision making. It is proposed that meta-rules can help resolve tensions arising from conflicting priorities between academics, knowledge transfer offices and industry and help facilitate strategic alignment of processes and policies within and between organisations. This research contributes to the growing debate on the strategic challenges of managing knowledge transfer and presents meta-rules as a practical solution to facilitate strategic alignment of internal and external stakeholder tensions. Meta-rules has previously only been applied in a computer intelligence context however, this research proves the efficacy of meta rules in a university–industry knowledge transfer context. This research also has practical implications for knowledge transfer office managers who can use meta-rules to help overcome resource limitations, conflicting priorities and goals of diverse internal and external stakeholders

Investigating the use of sensor-based IoET to facilitate learning for children in rural Thailand

A novel sensor-based Internet of Educational Things (IoET) platform named OBSY was iteratively designed, developed and evaluated to support education in rural regions in Thailand. To assess the effectiveness of this platform, a study was carried out at four primary schools located near the Thai northern border with 244 students and 8 teachers. Participants were asked to carry out three science-based learning activities and were measured for improvements in learning outcome and learning engagement. Overall, the results showed that students in the IoET group who had used OBSY to learn showed significantly higher learning outcome and had better learning engagement than those in the control condition. In addition, for those in the IoET group, there was no significant effect regarding gender, home location (Urban or Rural), age, prior experience with technology and ethnicity on learning outcome. For learning engagement, only age was found to influence interest/enjoyment. The study demonstrated the potential of IoET technologies in underprivileged area, through a co-design approach with teachers and students, taking into account the local contexts

Why walkers slip: shine is not a reliable cue for slippery ground.

In a series of four studies, we investigated the visual cues that walkers use to predict slippery ground surfaces and tested whether visual information is reliable for specifying low-friction conditions. In Study 1, 91% of participants surveyed responded that they would use shine to identify upcoming slippery ground. Studies 2-4 confirmed participants' reliance on shine to predict slip. Participants viewed ground surfaces varying in gloss, paint color, and viewing distance under indoor and outdoor lighting conditions. Shine and slip ratings and functional walking judgments were related to surface gloss level and to surface coefficient of friction (COF). However, judgments were strongly affected by surface color, viewing distance, and lighting conditions--extraneous factors that do not change the surface COF. Results suggest that, although walkers rely on shine to predict slippery ground, shine is not a reliable visual cue for friction. Poor visual information for friction may underlie the high prevalence of friction-related slips and falls

Insulin-like growth factor I is expressed in classical and nodular lymphocyte-predominant Hodgkin's lymphoma tumour and microenvironmental cells

Hodgkin's lymphoma (HL) is among the most frequent nodal lymphomas in the Western world and is classified into two disease entities: nodular lymphocyte-predominant Hodgkin's lymphoma (NLPHL) and classical Hodgkin's lymphoma (cHL, 95 % of all HL). HL lesions are characterised by a minority of clonal neoplastic cells, namely Hodgkin and Reed-Sternberg (HRS) cells and their variants in cHL and lymphocyte-predominant (LP) cells in NLPHL, both occurring within a microenvironment of, for example, reactive T and B cells, macrophages and granulocytes that are assumed to support the proliferation and maintenance of neoplastic cells through cytokines, chemokines and growth factors. Insulin-like growth factor I (IGF-I) is an important growth factor involved in proliferation, differentiation, apoptosis and cell survival of numerous (including immune) tissues and probably has a role in tumour pathogenesis and maintenance. Although HL is characterised by disturbed cell differentiation and apoptosis mechanisms, with the involvement of the IGF-I receptor (IGF-1R), the distinct location of IGF-I in HL has not yet been defined. We localise IGF-I by double-immunofluorescence in frequent neoplastic cells of all cHL and NLPHL cases investigated. Additionally, IGF-I immunoreactivity is detected in high endothelial venules and various immune cells within the surrounding tissue of cHL including neutrophils and macrophages. IGF-1R immunoreactivity of variable intensity is found in HRS cells and high endothelial venules within the microenvironment in cHL. We assume that autocrine and paracrine IGF-I plays an anti-apoptotic role in tumour pathogenesis and in shaping the tumour microenvironment

Strategic and Managerial Decision-Making for Sustainable Management: Factors and Remedies for Information Overload

In the past century, the amount of information that is generated has increased at an exponential rate. As a result of this information saturation process or ‘information overload’, people cannot keep pace with the information flowing towards them. Organizations can take steps towards sustainability by improving the health conditions in their organizations and the products they offer. One way to do so is by trying to reduce information overload. Besides improving health conditions, decreasing information overload also positively affects the quality of organizational-level decision-making. This is a conceptual chapter in which propositions are built. The determinants of information overload and the effect on decision quality are described, and an extensive literature review is conducted. The chapter draws from decision theory and the theory of human information processing and focuses on the individual characteristics of decision-makers and the quality of the information provided by the information system. Seven propositions are formulated and several remedies for information overload are discussed. The chapter arrives at two determinants of an individual’s degree of information overload experienced (characteristics of the decision-maker and the information system), and it is argued that information overload has a negative influence on the quality of decisions. These concepts are combined in one model. The conceptual model is an attempt to provide a better theoretical understanding of the concept of information overload. Finally, contributions, limitations and areas for future research are discussed.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Economics of Technology and Innovatio