A brain-inspired cognitive system that mimics the dynamics of human thought

In recent years, some impressive AI systems have been built that can play games and answer questions about large quantities of data. However, we are still a very long way from AI systems that can think and learn in a human-like way. We have a great deal of information about how the brain works and can simulate networks of hundreds of millions of neurons. So it seems likely that we could use our neuroscientific knowledge to build brain-inspired artificial intelligence that acts like humans on similar timescales. This paper describes an AI system that we have built using a brain-inspired network of artificial spiking neurons. On a word recognition and colour naming task our system behaves like human subjects on a similar timescale. In the longer term, this type of AI technology could lead to more flexible general purpose artificial intelligence and to more natural human-computer interaction

Internal brand co-creation: the experiential brand meaning cycle in higher education

Higher education (HE) institutions need to adapt to the global environment but the complex nature of HE highlights the role of marketing and the internal market in realizing the brand identity, creating a challenge for developing a shared brand meaning. This research explores how employees co-create brand meaning through their brand experiences and social interactions with management, colleagues and customers. Using a phenomenological approach, the findings highlight that brand meaning commences from historical, superficial brand interactions. Employees then develop brand meaning further through a series of brand interactions and social interactions. Bridging the internal branding and the co-creation literature, this study conceptualizes the evolving, co-created nature of employees' brand meaning in the experiential brand meaning cycle. This study extends Iglesias and Bonet's (2012) work and illustrates the function of employees as readers and authors of brand meaning, emphasizing the crucial role of brand co-creation in guiding employees' brand promise delivery

Nonlinear dimensionality reduction in climate data

Linear methods of dimensionality reduction are useful tools for handling and interpreting high dimensional data. However, the cumulative variance explained by each of the subspaces in which the data space is decomposed may show a slow convergence that makes the selection of a proper minimum number of subspaces for successfully representing the variability of the process ambiguous. The use of nonlinear methods can improve the embedding of multivariate data into lower dimensional manifolds. In this article, a nonlinear method for dimensionality reduction, Isomap, is applied to the sea surface temperature and thermocline data in the tropical Pacific Ocean, where the El Niño-Southern Oscillation (ENSO) phenomenon and the annual cycle phenomena interact. Isomap gives a more accurate description of the manifold dimensionality of the physical system. The knowledge of the minimum number of dimensions is expected to improve the development of low dimensional models for understanding and predicting ENSO

Environmental effects on galaxy evolution. II: quantifying the tidal features in NIR-images of the cluster Abell 85

This work is part of a series of papers devoted to investigate the evolution of cluster galaxies during their infall. In the present article we imaged in NIR a selected sample of galaxies through- out the massive cluster Abell 85 (z = 0.055). We obtained (JHK) photometry for 68 objects, reaching 1 mag/arcsec^2 deeper than 2MASS. We use these images to unveil asymmetries in the outskirts of a sample of bright galaxies and develop a new asymmetry index, alpha_An, which allows to quantify the degree of disruption by the relative area occupied by the tidal features on the plane of the sky. We measure the asymmetries for a subsample of 41 large area objects finding clear asymmetries in ten galaxies, most of them being in groups and pairs projected at different clustercentric distances, some of them located beyond R500 . Combining information on the Hi-gas content of blue galaxies and the distribution of sub-structures across Abell 85, with the present NIR asymmetry analysis, we obtain a very powerful tool to confirm that tidal mechanisms are indeed present and are currently affecting a fraction of galaxies in Abell 85. However, when comparing our deep NIR images with UV-blue images of two very disrupted (jellyfish) galaxies in this cluster, we discard the presence of tidal 1 interactions down to our detection limit. Our results suggest that ram-pressure stripping is at the origin of such spectacular disruptions. We conclude that across a complex cluster like Abell 85, environment mechanisms, both gravitational and hydrodynamical, are playing an active role in driving galaxy evolution.Comment: 30 pages, 13 figures, Accepted for Publication in A

Estimating the benefits of dedicated unloading bays by field experimentation

In most dense urban environments in emerging markets, retail deliveries are very fragmented to thousands of nanostores. It is not uncommon for a delivery route to include more than 60 stops. Unloading bays are often blocked by regular traffic. Due to the complex urban environment, it is difficult to estimate the benefits of making unloading bays available. In this study, we conduct a field experiment in an urban field lab of one square kilometer in the downtown of Querétaro, Mexico. During the treatment period of one week, we obtain help from the local traffic police to keep the unloading bays available for unloading only. Using advanced GPS devices and extensive manual field observations, we are able to capture the change in driver behavior and the direct efficiency increases. We find a high efficiency gain, not only in travel time (39%) but also – remarkably – in the total time parked (17%). Corrected for other effects, we estimate a gain of about 44% in total time per delivery. Apart from the insights on unloading benefits, we also provide insights into the method of field experimentation in such a complex environment

Comparison of predator-parasitoid-prey interaction models for different host plant qualities

Population dynamics models suggest that the over-all level of resource productivity plays an important role in community dynamics. One such factor of resource productivity is the quality of the host plant, which can determine the effectiveness of entomophagous (predatory and parasitoid) species by altering the growth rate of the phytophagous population via effects on fecundity, survival, and rate of development. These effects have been studied in relation to the distribution of host plants and their physiological state. However, few studies have considered the differences among plant cultivars. The objective of this study was to identify a continuous-time dynamic model, to describe the effects of different tomato cultivars on a one predatortwo prey model. The experiment was carried out under greenhouse conditions using ten tomato cultivars, with the predatory species Nesidiocoris tenuis (Reuter) (Insecta, Hemiptera, Miridae) and two prey species: the phytophagous species Bemisia tabaci (Gennadius) (Insecta, Hemiptera, Aleyrodidae) and the parasitoid species Trichogramma achaeae (Nagaraja & Nagarkatti) (Insecta, Hymenoptera, Trichogrammatidae); the latter was used as the intraguild-prey. Using the software SIMFIT, we found that a three-dimensional Lotka-Volterra type system could be well fitted to the data, estimating the phytophagous species´ growth rate, the parasitoid and predator mortality rates, the predation and parasitism rates, and the parasitoid emergence rate according to the cultivar type. The results showed an important effect of the host plant quality, by cultivar, on intraguild predation, resulting in important changes in the dynamics of phytophagous populations. These results are also discussed in relation to their importance in the biological control of pest species in greenhouse crops

The Effects of High-Intensity Interval Training versus Steady-State Training on Body Fat and Fat Oxidation

Please view abstract in the attached PDF fil