Chemical, bacteriological and sensory examination of split, dried, smoked bream on the market in Zambia

A critical examination of the market quality of split, dried and smoked bream (Tilapia spp.) was chemically, bacteriologically and organoleptically conducted for the period of August 1968 to January 1969. The aim of this survey was to obtain basic information for the development of national quality standards for the commodity. Relationships of cooked meat score to pH, fish size, appearance and smell score, and water content wcre significantly correlated and responsive. Therefore, these parameters were proposed to be used as indices for the quality standards of the products.

Beyond niche thinking: Market selection in science-based ventures

Matching a new technology to an appropriate market is a major challenge for new technology-based firms (NTBF). Such firms are often advised to target niche-markets where the firms and their technologies can establish themselves relatively free of incumbent competition. However, technologies are diverse in nature and do not benefit from identical strategies. In contrast to many Information and Communication Technology (ICT) innovations which build on an established knowledge base for fairly specific applications, technologies based on emerging science are often generic and so have a number of markets and applications open to them, each carrying considerable technological and market uncertainty. Each of these potential markets is part of a complex and evolving ecosystem from which the venture may have to access significant complementary assets in order to create and sustain commercial value. Based on dataset and case study research on UK advanced material university spin-outs (USO), we find that, contrary to conventional wisdom, the more commercially successful ventures were targeting mainstream markets by working closely with large, established competitors during early development. While niche markets promise protection from incumbent firms, science-based innovations, such as new materials, often require the presence, and participation, of established companies in order to create value. © 2012 IEEE.

Internal representations of temporal statistics and feedback calibrate motor-sensory interval timing.

Humans have been shown to adapt to the temporal statistics of timing tasks so as to optimize the accuracy of their responses, in agreement with the predictions of Bayesian integration. This suggests that they build an internal representation of both the experimentally imposed distribution of time intervals (the prior) and of the error (the loss function). The responses of a Bayesian ideal observer depend crucially on these internal representations, which have only been previously studied for simple distributions. To study the nature of these representations we asked subjects to reproduce time intervals drawn from underlying temporal distributions of varying complexity, from uniform to highly skewed or bimodal while also varying the error mapping that determined the performance feedback. Interval reproduction times were affected by both the distribution and feedback, in good agreement with a performance-optimizing Bayesian observer and actor model. Bayesian model comparison highlighted that subjects were integrating the provided feedback and represented the experimental distribution with a smoothed approximation. A nonparametric reconstruction of the subjective priors from the data shows that they are generally in agreement with the true distributions up to third-order moments, but with systematically heavier tails. In particular, higher-order statistical features (kurtosis, multimodality) seem much harder to acquire. Our findings suggest that humans have only minor constraints on learning lower-order statistical properties of unimodal (including peaked and skewed) distributions of time intervals under the guidance of corrective feedback, and that their behavior is well explained by Bayesian decision theory.

Market-pull and technology-push in manufacturing start-ups in emerging industries

Purpose - As traditional manufacturing, previously vital to the UK economy, is increasingly outsourced to lower-cost locations, policy makers seek leadership in emerging industries by encouraging innovative start-up firms to pursue competitive opportunities. Emerging industries can either be those where a technology exists but the corresponding downstream value chain is unclear, or a new technology may subvert the existing value chain to satisfy existing customer needs. Hence, this area shows evidence of both technology-push and market-pull forces. The purpose of this paper is to focus on market-pull and technology-push orientations in manufacturing ventures, specifically examining how and why this orientation shifts during the firm's formative years. Design/methodology/approach - A multiple case study approach of 25 UK start-ups in emerging industries is used to examine this seldom explored area. The authors offer two models of dynamic business-orientation in start-ups and explain the common reasons for shifts in orientation and why these two orientations do not generally co-exist during early firm development. Findings - Separate evolution paths were found for strategic orientation in manufacturing start-ups and separate reasons for them to shift in their early development. Technology-push start-ups often changed to a market-pull orientation because of new partners, new market information or shift in management priorities. In contrast, many of the start-ups beginning with a market-pull orientation shifted to a technology-push orientation because early market experiences necessitated a focus on improving processes in order to increase productivity or meet partner specifications, or meet a demand for complementary products. Originality/value - While a significant body of work exists regarding manufacturing strategy in established firms, little work has been found that investigates how manufacturing strategy emerges in start-up companies, particularly those in emerging industries. © Emerald Group Publishing Limited.

Functional requirements for reward-modulated spike-timing-dependent plasticity.

Recent experiments have shown that spike-timing-dependent plasticity is influenced by neuromodulation. We derive theoretical conditions for successful learning of reward-related behavior for a large class of learning rules where Hebbian synaptic plasticity is conditioned on a global modulatory factor signaling reward. We show that all learning rules in this class can be separated into a term that captures the covariance of neuronal firing and reward and a second term that presents the influence of unsupervised learning. The unsupervised term, which is, in general, detrimental for reward-based learning, can be suppressed if the neuromodulatory signal encodes the difference between the reward and the expected reward-but only if the expected reward is calculated for each task and stimulus separately. If several tasks are to be learned simultaneously, the nervous system needs an internal critic that is able to predict the expected reward for arbitrary stimuli. We show that, with a critic, reward-modulated spike-timing-dependent plasticity is capable of learning motor trajectories with a temporal resolution of tens of milliseconds. The relation to temporal difference learning, the relevance of block-based learning paradigms, and the limitations of learning with a critic are discussed.

Slowness: an objective for spike-timing-dependent plasticity?

Our nervous system can efficiently recognize objects in spite of changes in contextual variables such as perspective or lighting conditions. Several lines of research have proposed that this ability for invariant recognition is learned by exploiting the fact that object identities typically vary more slowly in time than contextual variables or noise. Here, we study the question of how this "temporal stability" or "slowness" approach can be implemented within the limits of biologically realistic spike-based learning rules. We first show that slow feature analysis, an algorithm that is based on slowness, can be implemented in linear continuous model neurons by means of a modified Hebbian learning rule. This approach provides a link to the trace rule, which is another implementation of slowness learning. Then, we show analytically that for linear Poisson neurons, slowness learning can be implemented by spike-timing-dependent plasticity (STDP) with a specific learning window. By studying the learning dynamics of STDP, we show that for functional interpretations of STDP, it is not the learning window alone that is relevant but rather the convolution of the learning window with the postsynaptic potential. We then derive STDP learning windows that implement slow feature analysis and the "trace rule." The resulting learning windows are compatible with physiological data both in shape and timescale. Moreover, our analysis shows that the learning window can be split into two functionally different components that are sensitive to reversible and irreversible aspects of the input statistics, respectively. The theory indicates that irreversible input statistics are not in favor of stable weight distributions but may generate oscillatory weight dynamics. Our analysis offers a novel interpretation for the functional role of STDP in physiological neurons.

Timing feedback control of a rhythmic system

This paper addresses the question relative to the role of sensory feedback in rhythmic tasks. We study the properties of a sinusoidally vibrating wedge-billiard as a model for 2-D bounce juggling. If this wedge is actuated with an harmonic sinusoidal input, it has been shown that some periodic orbits are exponentially stable. This paper explores an intuitive method to enlarge the parametric stability region of the simplest of these orbits. Accurate processing of timing is proven to be an important key to achieve frequency-locking in rhythmic tasks. © 2005 IEEE.

Inhibitory Synaptic Plasticity - Spike timing dependence and putative network function.

While the plasticity of excitatory synaptic connections in the brain has been widely studied, the plasticity of inhibitory connections is much less understood. Here, we present recent experimental and theoretical □ndings concerning the rules of spike timing-dependent inhibitory plasticity and their putative network function. This is a summary of a workshop at the COSYNE conference 2012.

Design and market considerations for axial flux superconducting electric machine design

In this paper, the authors investigate a number of design and market considerations for an axial flux superconducting electric machine design that uses high temperature superconductors. The axial flux machine design is assumed to utilise high temperature superconductors in both wire (stator winding) and bulk (rotor field) forms, to operate over a temperature range of 65-77 K, and to have a power output in the range from 10s of kW up to 1 MW (typical for axial flux machines), with approximately 2-3 T as the peak trapped field in the bulk superconductors. The authors firstly investigate the applicability of this type of machine as a generator in small- and medium-sized wind turbines, including the current and forecasted market and pricing for conventional turbines. Next, a study is also carried out on the machine's applicability as an in-wheel hub motor for electric vehicles. Some recommendations for future applications are made based on the outcome of these two studies. Finally, the cost of YBCO-based superconducting (2G HTS) wire is analysed with respect to competing wire technologies and compared with current conventional material costs and current wire costs for both 1G and 2G HTS are still too great to be economically feasible for such superconducting devices.

A technology roadmap of assistive technologies for dementia care in Japan.

The number of elderly people in Japan is growing, which raises the issue of dementia, as the probability of becoming cognitively impaired increases with age. There is an increasing need for caregivers, who are well-trained, experienced and can pay special attention to the needs of people with dementia. Technology can play an important role in helping such people and their caregivers. A lack of mutual understanding between caregivers and researchers regarding the appropriate uses of assistive technologies is another problem. A vision of person-centred care based on the use of information and communication technology to maintain residents' autonomy and continuity in their lives is presented. Based on this vision, a roadmap and a list of challenges to realizing assistive technologies have been developed. The roadmap facilitates mutual understanding between caregivers and researchers, resulting in appropriate technologies to enhance the quality of life of people with dementia.

Innovation, the diesel engine and vehicle markets: Evidence from OECD engine patents

This paper uses a patent data set to identify factors fostering innovation of diesel engines between 1974 and 2010 in the OECD region. The propensity of engine producers to innovate grew by 1.9 standard deviations after the expansion of the car market, by 0.7 standard deviations following a shift in the EU fuel economy standard, and by 0.23 standard deviations. The propensity to develop emissions control techniques was positively influenced by pollution control laws introduced in Japan, in the US, and in the EU, but not with the expansion of the car market. Furthermore, a decline in loan rates stimulated the propensity to develop emissions control techniques, which were simultaneously crowded out by increases in publicly-funded transport research and development. Innovation activities in engine efficiency are explained by market size, loan rates and by (Organisation for Economic Cooperation and Development) diesel prices, inclusive of taxes. Price effects on innovation, outweigh that of the US corporate average fuel economy standards. Innovation is also positively influenced by past transport research and development. © 2014 Elsevier Ltd.