Practicing at Home: Computers, Pianos, and Cultural Capital

Part of the Volume on Digital Young, Innovation, and the Unexpected Bourdieu focused attention on the role of education and the influence of status distinctions on the selection and valorization of particular forms of cultural capital. Although Bourdieu did not write about digital media, he was a keen observer of status distinctions in education and how these translate into job markets. Through an extended analogy between learning the piano and learning the computer, I demonstrate Bourdieu's relevance for an expanded vision of digital literacy -- one that would forefront the material and social inequalities in U.S. domestic Internet access and in public education. High Tech High School, supported by the Gates Foundation, provides a case of why it is important to examine current digital pedagogy in terms of unarticulated and implicit models of entrepreneurial labor, both because these set up unrealistic expectations and because they can express corporate norms rather than critical pedagogy

Temperature sensitivity of the pyloric neuromuscular system and its modulation by dopamine

We report here the effects of temperature on the p1 neuromuscular system of the stomatogastric system of the lobster (Panulirus interruptus). Muscle force generation, in response to both the spontaneously rhythmic in vitro pyloric network neural activity and direct, controlled motor nerve stimulation, dramatically decreased as temperature increased, sufficiently that stomach movements would very unlikely be maintained at warm temperatures. However, animals fed in warm tanks showed statistically identical food digestion to those in cold tanks. Applying dopamine, a circulating hormone in crustacea, increased muscle force production at all temperatures and abolished neuromuscular system temperature dependence. Modulation may thus exist not only to increase the diversity of produced behaviors, but also to maintain individual behaviors when environmental conditions (such as temperature) vary

Zur Industriepolitk in Europa

Both the increasing mobility of capital and the globalization of enterprises has changed world markets in the last two decades. The economies of South-East Asia, especially Japan and South Korea, are no longer the work benches of the western industries, but they were very successful in catching up to the former leading nations of Europe and the United States. This development gave rise to a new discussion on the effects of industrial policy. One of the main shortcomings of this debate is the lack of a comprehensive analysis of all relevant decisions and measures. Since 1990 the Commission of the European Union (EU) has published several papers containing the objectives and instruments of a new industrial policy. The intention is to improve the competitiveness of the European firms and the creation of about 15 million jobs until the end of the century. For this reason the Commission wants to encourage non-physical investment to shift the physical-based economy to a knowledge-based economy. R&D efforts should be better coordinated and economic incentives to support the diffusion of R&D results into products and processes have to be applied. Another key element of these initiatives is the implementation of the so-called transeuropean networks (i.e. transport infrastructure, telecommunications and energy networks). Subsidies for ailing industries will be reduced while the future technologies will be promoted for their positive externalities on other sectors. The Commission lays particular stress on the Single Market as a kind of training field for the European industries, too. Competitive home markets are a necessary prerequisite for being internationally successful. A closer look at the main trading partners of the EU, Japan and the USA, shows that the governments of both countries pursue similiar strategies. The concept of a new industrial policy which takes into consideration the positive dynamic effects of competition could be justified by the results of the New (or Endogenous) Growth Theory. Particularly the externalities of investment decisions and the incentives to concentrate on R&D are analyzed. Studies like the famous one by Michael Porter or the ideas of Robert Reich reveal the increased importance of non-physical investment and competition, too. As a matter of fact the planned measures of the Commission seem to be a step in the right direction for their emphasis on improving the long-run growth conditions and for making the EU countries a more attractive location for international enterprises. Higher growth rates will offer the chance to create new jobs but in the short run this will not solve the current labour market problems. For leading economies (e.g. Germany) one element of a strategy to overcome these difficulties could be the choice between a more productivity-oriented or a more employment-oriented growth path within the sectors producing non-tradable goods. The second element is the reduction of working hours per head. This decrease could be combined with human capital investments. Reduced income could be compensated by a better qualification of the employees which lowers the probability of being laid off

Unsupervised online activity discovery using temporal behaviour assumption

We present a novel unsupervised approach, UnADevs, for discovering activity clusters corresponding to periodic and stationary activities in streaming sensor data. Such activities usually last for some time, which is exploited by our method; it includes mechanisms to regulate sensitivity to brief outliers and can discover multiple clusters overlapping in time to better deal with deviations from nominal behaviour. The method was evaluated on two activity datasets containing large number of activities (14 and 33 respectively) against online agglomerative clustering and DBSCAN. In a multi-criteria evaluation, our approach achieved significantly better performance on majority of the measures, with the advantages that: (i) it does not require to specify the number of clusters beforehand (it is open ended); (ii) it is online and can find clusters in real time; (iii) it has constant time complexity; (iv) and it is memory efficient as it does not keep the data samples in memory. Overall, it has managed to discover 616 of the total 717 activities. Because it discovers clusters of activities in real time, it is ideal to work alongside an active learning system