Towards Machine Consciousness: Grounding Abstract Models as pi-Processes

We present a two-level model of concurrent communicating systems (CCS) to serve as a basis formachine consciousness. A language implementing threads within logic programming is ¯rstintroduced. This high-level framework allows for the de¯nition of abstract processes that can beexecuted on a virtual machine. We then look for a possible grounding of these processes into thebrain. Towards this end, we map abstract de¯nitions (including logical expressions representingcompiled knowledge) into a variant of the pi-calculus. We illustrate this approach through aseries of examples extending from a purely reactive behavior to patterns of consciousness.

Timing of Capacity Change: Models for Capital Intensive Industry

The suitable timing of capacity investments is a remarkable issue especially in capital intensive industries. Despite its importance, fairly few studies have been published on the topic. In the present study models for the timing of capacity change in capital intensive industry are developed. The study considers mainly the optimal timing of single capacity changes. The review of earlier research describes connections between cost, capacity and timing literature, and empirical examples are used to describe the starting point of the study and to test the developed models. The study includes four models, which describe the timing question from different perspectives. The first model, which minimizes unit costs, has been built for capacity expansion and replacement situations. It is shown that the optimal timing of an investment can be presented with the capacity and cost advantage ratios. After the unit cost minimization model the view is extended to the direction of profit maximization. The second model states that early investments are preferable if the change of fixed costs is small compared to the change of the contribution margin. The third model is a numerical discounted cash flow model, which emphasizes the roles of start-up time, capacity utilization rate and value of waiting as drivers of the profitable timing of a project. The last model expands the view from project level to company level and connects the flexibility of assets and cost structures to the timing problem. The main results of the research are the solutions of the models and analysis or simulations done with the models. The relevance and applicability of the results are verified by evaluating the logic of the models and by numerical cases.

Forecasting tourism demand to Catalonia: neural networks vs. time series models

The increasing interest aroused by more advanced forecasting techniques, together with the requirement for more accurate forecasts of tourismdemand at the destination level due to the constant growth of world tourism, has lead us to evaluate the forecasting performance of neural modelling relative to that of time seriesmethods at a regional level. Seasonality and volatility are important features of tourism data, which makes it a particularly favourable context in which to compare the forecasting performance of linear models to that of nonlinear alternative approaches. Pre-processed official statistical data of overnight stays and tourist arrivals fromall the different countries of origin to Catalonia from 2001 to 2009 is used in the study. When comparing the forecasting accuracy of the different techniques for different time horizons, autoregressive integrated moving average models outperform self-exciting threshold autoregressions and artificial neural network models, especially for shorter horizons. These results suggest that the there is a trade-off between the degree of pre-processing and the accuracy of the forecasts obtained with neural networks, which are more suitable in the presence of nonlinearity in the data. In spite of the significant differences between countries, which can be explained by different patterns of consumer behaviour,we also find that forecasts of tourist arrivals aremore accurate than forecasts of overnight stays.

Three-Dimensional (3D) Microarchitecture Correlations with 2D Projection Image Gray-Level Variations Assessed by Trabecular Bone Score Using High-Resolution Computed Tomographic Acquisitions: Effects of Resolution and Noise.

The aim of the present study is to determine the level of correlation between the 3-dimensional (3D) characteristics of trabecular bone microarchitecture, as evaluated using microcomputed tomography (μCT) reconstruction, and trabecular bone score (TBS), as evaluated using 2D projection images directly derived from 3D μCT reconstruction (TBSμCT). Moreover, we have evaluated the effects of image degradation (resolution and noise) and X-ray energy of projection on these correlations. Thirty human cadaveric vertebrae were acquired on a microscanner at an isotropic resolution of 93μm. The 3D microarchitecture parameters were obtained using MicroView (GE Healthcare, Wauwatosa, MI). The 2D projections of these 3D models were generated using the Beer-Lambert law at different X-ray energies. Degradation of image resolution was simulated (from 93 to 1488μm). Relationships between 3D microarchitecture parameters and TBSμCT at different resolutions were evaluated using linear regression analysis. Significant correlations were observed between TBSμCT and 3D microarchitecture parameters, regardless of the resolution. Correlations were detected that were strongly to intermediately positive for connectivity density (0.711≤r(2)≤0.752) and trabecular number (0.584≤r(2)≤0.648) and negative for trabecular space (-0.407 ≤r(2)≤-0.491), up to a pixel size of 1023μm. In addition, TBSμCT values were strongly correlated between each other (0.77≤r(2)≤0.96). Study results show that the correlations between TBSμCT at 93μm and 3D microarchitecture parameters are weakly impacted by the degradation of image resolution and the presence of noise.

Are R&D collaborative agreements persistent at the firm level? Empirical evidence for the Spanish case

We provide evidence on the dynamics in firms’ R&D cooperation behaviour. Our main objective is to analyse if R&D collaborative agreements are persistent at the firm level, and in such a case, to study what are the main drivers of this phenomenon. R&D cooperation activities at the firm level can be persistent due to true state dependence, this implying that cooperating in a given period enhances the probability of doing it in the subsequent period and it can also be a consequence of firms’ individual heterogeneity, so that certain firms have certain characteristics that make them more likely to carry out technological alliances.

Are R&D collaborative agreements persistent at the firm level? Empirical evidence for the Spanish case

We provide evidence on the dynamics in firms’ R&D cooperation behaviour. Our main objective is to analyse if R&D collaborative agreements are persistent at the firm level, and in such a case, to study what are the main drivers of this phenomenon. R&D cooperation activities at the firm level can be persistent due to true state dependence, this implying that cooperating in a given period enhances the probability of doing it in the subsequent period and it can also be a consequence of firms’ individual heterogeneity, so that certain firms have certain characteristics that make them more likely to carry out technological alliances.

Solution scanning as a key policy tool: identifying management interventions to help maintain and enhance regulating ecosystem services

The major task of policy makers and practitioners when confronted with a resource management problem is to decide on the potential solution(s) to adopt from a range of available options. However, this process is unlikely to be successful and cost effective without access to an independently verified and comprehensive available list of options. There is currently burgeoning interest in ecosystem services and quantitative assessments of their importance and value. Recognition of the value of ecosystem services to human well-being represents an increasingly important argument for protecting and restoring the natural environment, alongside the moral and ethical justifications for conservation. As well as understanding the benefits of ecosystem services, it is also important to synthesize the practical interventions that are capable of maintaining and/or enhancing these services. Apart from pest regulation, pollination, and global climate regulation, this type of exercise has attracted relatively little attention. Through a systematic consultation exercise, we identify a candidate list of 296 possible interventions across the main regulating services of air quality regulation, climate regulation, water flow regulation, erosion regulation, water purification and waste treatment, disease regulation, pest regulation, pollination and natural hazard regulation. The range of interventions differs greatly between habitats and services depending upon the ease of manipulation and the level of research intensity. Some interventions have the potential to deliver benefits across a range of regulating services, especially those that reduce soil loss and maintain forest cover. Synthesis and applications: Solution scanning is important for questioning existing knowledge and identifying the range of options available to researchers and practitioners, as well as serving as the necessary basis for assessing cost effectiveness and guiding implementation strategies. We recommend that it become a routine part of decision making in all environmental policy areas.

Ten years after the Prestige Oil Spill: seabird trophic ecology as indicator of long-term effects on the coastal marine ecosystem

Major oil spills can have long-term impacts since oil pollution does not only result in acute mortality of marine organisms, but also affects productivity levels, predator-prey dynamics, and damages habitats that support marine communities. However, despite the conservation implications of oil accidents, the monitoring and assessment of its lasting impacts still remains a difficult and daunting task. Here, we used European shags to evaluate the overall, lasting effects of the Prestige oil spill (2002) on the affected marine ecosystem. Using δ15N and Hg analysis, we trace temporal changes in feeding ecology potentially related to alterations of the food web due to the spill. Using climatic and oceanic data, we also investigate the influence of North Atlantic Oscillation (NAO) index, the sea surface temperature (SST) and the chlorophyll a (Chl a) on the observed changes. Analysis of δ15N and Hg concentrations revealed that after the Prestige oil spill, shag chicks abruptly switched their trophic level from a diet based on a high percentage of demersal-benthic fish to a higher proportion of pelagic/semi-pelagic species. There was no evidence that Chl a, SST and NAO reflected any particular changes or severity in environmental conditions for any year or season that may explain the sudden change observed in trophic level. Thus, this study highlighted an impact on the marine food web for at least three years. Our results provide the best evidence to date of the long-term consequences of the Prestige oil spill. They also show how, regardless of wider oceanographic variability, lasting impacts on predator-prey dynamics can be assessed using biochemical markers. This is particularly useful if larger scale and longer term monitoring of all trophic levels is unfeasible due to limited funding or high ecosystem complexity.

Evolutionary Games in Networked Populations: Models and Experiments

Cooperation and coordination are desirable behaviors that are fundamental for the harmonious development of society. People need to rely on cooperation with other individuals in many aspects of everyday life, such as teamwork and economic exchange in anonymous markets. However, cooperation may easily fall prey to exploitation by selfish individuals who only care about short- term gain. For cooperation to evolve, specific conditions and mechanisms are required, such as kinship, direct and indirect reciprocity through repeated interactions, or external interventions such as punishment. In this dissertation we investigate the effect of the network structure of the population on the evolution of cooperation and coordination. We consider several kinds of static and dynamical network topologies, such as Baraba´si-Albert, social network models and spatial networks. We perform numerical simulations and laboratory experiments using the Prisoner's Dilemma and co- ordination games in order to contrast human behavior with theoretical results. We show by numerical simulations that even a moderate amount of random noise on the Baraba´si-Albert scale-free network links causes a significant loss of cooperation, to the point that cooperation almost vanishes altogether in the Prisoner's Dilemma when the noise rate is high enough. Moreover, when we consider fixed social-like networks we find that current models of social networks may allow cooperation to emerge and to be robust at least as much as in scale-free networks. In the framework of spatial networks, we investigate whether cooperation can evolve and be stable when agents move randomly or performing Le´vy flights in a continuous space. We also consider discrete space adopting purposeful mobility and binary birth-death process to dis- cover emergent cooperative patterns. The fundamental result is that cooperation may be enhanced when this migration is opportunistic or even when agents follow very simple heuristics. In the experimental laboratory, we investigate the issue of social coordination between indi- viduals located on networks of contacts. In contrast to simulations, we find that human players dynamics do not converge to the efficient outcome more often in a social-like network than in a random network. In another experiment, we study the behavior of people who play a pure co- ordination game in a spatial environment in which they can move around and when changing convention is costly. We find that each convention forms homogeneous clusters and is adopted by approximately half of the individuals. When we provide them with global information, i.e., the number of subjects currently adopting one of the conventions, global consensus is reached in most, but not all, cases. Our results allow us to extract the heuristics used by the participants and to build a numerical simulation model that agrees very well with the experiments. Our findings have important implications for policymakers intending to promote specific, desired behaviors in a mobile population. Furthermore, we carry out an experiment with human subjects playing the Prisoner's Dilemma game in a diluted grid where people are able to move around. In contrast to previous results on purposeful rewiring in relational networks, we find no noticeable effect of mobility in space on the level of cooperation. Clusters of cooperators form momentarily but in a few rounds they dissolve as cooperators at the boundaries stop tolerating being cheated upon. Our results highlight the difficulties that mobile agents have to establish a cooperative environment in a spatial setting without a device such as reputation or the possibility of retaliation. i.e. punishment. Finally, we test experimentally the evolution of cooperation in social networks taking into ac- count a setting where we allow people to make or break links at their will. In this work we give particular attention to whether information on an individual's actions is freely available to poten- tial partners or not. Studying the role of information is relevant as information on other people's actions is often not available for free: a recruiting firm may need to call a job candidate's refer- ences, a bank may need to find out about the credit history of a new client, etc. We find that people cooperate almost fully when information on their actions is freely available to their potential part- ners. Cooperation is less likely, however, if people have to pay about half of what they gain from cooperating with a cooperator. Cooperation declines even further if people have to pay a cost that is almost equivalent to the gain from cooperating with a cooperator. Thus, costly information on potential neighbors' actions can undermine the incentive to cooperate in dynamical networks.

Serum 25-hydroxyvitamin D level and kidney function decline in a Swiss general adult population.

Molecular evidence suggests that levels of vitamin D are associated with kidney function loss. Still, population-based studies are limited and few have considered the potential confounding effect of baseline kidney function. This study evaluated the association of serum 25-hydroxyvitamin D with change in eGFR, rapid eGFR decline, and incidence of CKD and albuminuria. Baseline (2003-2006) and 5.5-year follow-up data from a Swiss adult general population were used to evaluate the association of serum 25-hydroxyvitamin D with change in eGFR, rapid eGFR decline (annual loss >3 ml/min per 1.73 m(2)), and incidence of CKD and albuminuria. Serum 25-hydroxyvitamin D was measured at baseline using liquid chromatography-tandem mass spectrometry. eGFR and albuminuria were collected at baseline and follow-up. Multivariate linear and logistic regression models were used considering potential confounding factors. Among the 4280 people included in the analysis, the mean±SD annual eGFR change was -0.57±1.78 ml/min per 1.73 m(2), and 287 (6.7%) participants presented rapid eGFR decline. Before adjustment for baseline eGFR, baseline 25-hydroxyvitamin D level was associated with both mean annual eGFR change and risk of rapid eGFR decline, independently of baseline albuminuria. Once adjusted for baseline eGFR, associations were no longer significant. For every 10 ng/ml higher baseline 25-hydroxyvitamin D, the adjusted mean annual eGFR change was -0.005 ml/min per 1.73 m(2) (95% confidence interval, -0.063 to 0.053; P=0.87) and the risk of rapid eGFR decline was null (odds ratio, 0.93; 95% confidence interval, 0.79 to 1.08; P=0.33). Baseline 25-hydroxyvitamin D level was not associated with incidence of CKD or albuminuria. The association of 25-hydroxyvitamin D with eGFR decline is confounded by baseline eGFR. Sufficient 25-hydroxyvitamin D levels do not seem to protect from eGFR decline independently from baseline eGFR.

Factors Affecting the Forecasting Accuracy of Diffusion Models

Tutkielman tavoitteena oli tarkastella innovaatioiden leviämismallien ennustetarkkuuteen vaikuttavia tekijöitä. Tutkielmassa ennustettiin logistisella mallilla matkapuhelinliittymien leviämistä kolmessa Euroopan maassa: Suomessa, Ranskassa ja Kreikassa. Teoriaosa keskittyi innovaatioiden leviämisen ennustamiseen leviämismallien avulla. Erityisesti painotettiin mallien ennustuskykyä ja niiden käytettävyyttä eri tilanteissa. Empiirisessä osassa keskityttiin ennustamiseen logistisella leviämismallilla, joka kalibroitiin eri tavoin koostetuilla aikasarjoilla. Näin tehtyjä ennusteita tarkasteltiin tiedon kokoamistasojen vaikutusten selvittämiseksi. Tutkimusasetelma oli empiirinen, mikä sisälsi logistisen leviämismallin ennustetarkkuuden tutkimista otosdatan kokoamistasoa muunnellen. Leviämismalliin syötettävä data voidaan kerätä kuukausittain ja operaattorikohtaisesti vaikuttamatta ennustetarkkuuteen. Dataan on sisällytettävä leviämiskäyrän käännöskohta, eli pitkän aikavälin huippukysyntäpiste.

Mixed and Hybrid Models of Public Service Delivery

This symposium presents research from different contexts to improve our collective understanding of a variety of aspects of mixed forms of service delivery, be they mixed contracting at the level of the market (which is more common in the U.S.), or mixed management and ownership at the level of the firm (which is more common in Europe). The articles included in this special symposium examine the factors that give rise to mixed forms of service delivery (e.g., economic and fiscal stress, regulatory flexibility, geography, management) and how these factors impact their design and operation. Articles also explore the performance of mixed forms of service delivery relative to more conventional arrangements like contracted or direct service delivery. The articles contribute to a better theoretical and conceptual understanding of mixed/hybrid forms of services delivery.

Quantum chaos in SU(3) models with trapped ions

A scheme to generate long-range spin-spin interactions between three-level ions in a chain is presented, providing a feasible experimental route to the rich physics of well-known SU(3) models. In particular, we demonstrate different signatures of quantum chaos which can be controlled and observed in experiments with trapped ions.

What can ecosystems learn? Expanding evolutionary ecology with learning theory.

BACKGROUND: The structure and organisation of ecological interactions within an ecosystem is modified by the evolution and coevolution of the individual species it contains. Understanding how historical conditions have shaped this architecture is vital for understanding system responses to change at scales from the microbial upwards. However, in the absence of a group selection process, the collective behaviours and ecosystem functions exhibited by the whole community cannot be organised or adapted in a Darwinian sense. A long-standing open question thus persists: Are there alternative organising principles that enable us to understand and predict how the coevolution of the component species creates and maintains complex collective behaviours exhibited by the ecosystem as a whole? RESULTS: Here we answer this question by incorporating principles from connectionist learning, a previously unrelated discipline already using well-developed theories on how emergent behaviours arise in simple networks. Specifically, we show conditions where natural selection on ecological interactions is functionally equivalent to a simple type of connectionist learning, 'unsupervised learning', well-known in neural-network models of cognitive systems to produce many non-trivial collective behaviours. Accordingly, we find that a community can self-organise in a well-defined and non-trivial sense without selection at the community level; its organisation can be conditioned by past experience in the same sense as connectionist learning models habituate to stimuli. This conditioning drives the community to form a distributed ecological memory of multiple past states, causing the community to: a) converge to these states from any random initial composition; b) accurately restore historical compositions from small fragments; c) recover a state composition following disturbance; and d) to correctly classify ambiguous initial compositions according to their similarity to learned compositions. We examine how the formation of alternative stable states alters the community's response to changing environmental forcing, and we identify conditions under which the ecosystem exhibits hysteresis with potential for catastrophic regime shifts. CONCLUSIONS: This work highlights the potential of connectionist theory to expand our understanding of evo-eco dynamics and collective ecological behaviours. Within this framework we find that, despite not being a Darwinian unit, ecological communities can behave like connectionist learning systems, creating internal conditions that habituate to past environmental conditions and actively recalling those conditions. REVIEWERS: This article was reviewed by Prof. Ricard V Solé, Universitat Pompeu Fabra, Barcelona and Prof. Rob Knight, University of Colorado, Boulder.

Mother-offspring competition promotes colonization success.

Colonization is the crucial process underlying range expansions, biological invasions, and metapopulation dynamics. Which individuals leave their natal population to colonize empty habitats is a crucial question and is presently unresolved. Dispersal is the first step in colonization. However, not all dispersing individuals are necessarily good colonizers. Indeed, in some species, the phenotype of dispersers differs depending on the selective pressures that induce dispersal. In particular, kin-based interactions, a factor driving social evolution, should induce different social response profiles in nondispersing and dispersing individuals. Kin competition (defined here as between the mother and offspring) has been proven to produce dispersers with a particular phenotype that may enhance their colonizing ability. By using the common lizard (Lacerta vivipara), we conducted a multipopulation experiment to study the effect of kin competition on dispersal and colonization success. We manipulated mother-offspring interactions, which are the most important component of kin competition in the studied species, at the family and population levels and measured the consequences on colonization success. We demonstrate that mother-offspring competition at the population level significantly influences colonization success. Increased competition at the population level enhanced the colonization rate of the largest juveniles as well as the growth and survival of the colonizers. Based on these results, we calculated that kin-induced colonization halves the extinction probability of a newly initiated population. Because interactions between relatives are likely to affect the ability of a species to track habitat modifications, kin-based dispersal should be considered in the study of invasion dynamics and metapopulation functioning.