The comparative effectiveness of rodents and dung beetles as local seed dispersers in Mediterranean oak forests

The process of seed dispersal of many animal-dispersed plants is frequently mediated by a small set of biotic agents. However, the contribution that each of these dispersers makes to the overall recruitment may differ largely, with important ecological and management implications for the population viability and dynamics of the species implied in these interactions. In this paper, we compared the relative contribution of two local guilds of scatter-hoarding animals with contrasting metabolic requirements and foraging behaviours (rodents and dung beetles) to the overall recruitment of two Quercus species co-occurring in the forests of southern Spain. For this purpose, we considered not only the quantity of dispersed seeds but also the quality of the seed dispersal process. The suitability for recruitment of the microhabitats where the seeds were deposited was evaluated in a multi-stage demographic approach. The highest rates of seed handling and predation occurred in those microhabitats located under shrubs, mostly due to the foraging activity of rodents. However, the probability of a seed being successfully cached was higher in microhabitats located beneath a tree canopy as a result of the feeding behaviour of beetles. Rodents and beetles showed remarkable differences in their effectiveness as local acorn dispersers. Quantitatively, rodents were much more important than beetles because they dispersed the vast majority of acorns. However, they were qualitatively less effective because they consumed a high proportion of them (over 95%), and seeds were mostly dispersed under shrubs, a less suitable microhabitat for short-term recruitment of the two oak species. Our findings demonstrate that certain species of dung beetles (such as Thorectes lusitanicus), despite being quantitatively less important than rodents, can act as effective local seed dispersers of Mediterranean oak species. Changes in the abundance of beetle populations could thus have profound implications for oak recruitment and community dynamics.

Thermal decomposition of the different particles size fractions of almond shells and olive stones. Thermal behaviour changes due to the milling processes

The aim of this study is to investigate the effect of particle size on the non-isothermal pyrolysis of almond shells (AS) and olive stones (OS) and to show possible differences in the composition of the different fractions obtained after milling and sieving. The results obtained from the study of different particle size of AS and OS samples show significant differences in the solid residue obtained and in the shape and overlapping degree of the peaks, especially with the smaller particle size. These differences can be due to different factors: (a) the amount of inorganic matter, which increases as particle size decreases, (b) heat and mass transfer processes, (c) different sample composition as a consequence of the milling process which may provoke changes in the structure and the segregation of the components (in addition to the ashes) increasingly changes the composition of the sample as the particle size decreases.

Human Behaviour Recognition based on Trajectory Analysis using Neural Networks

Automated human behaviour analysis has been, and still remains, a challenging problem. It has been dealt from different points of views: from primitive actions to human interaction recognition. This paper is focused on trajectory analysis which allows a simple high level understanding of complex human behaviour. It is proposed a novel representation method of trajectory data, called Activity Description Vector (ADV) based on the number of occurrences of a person is in a specific point of the scenario and the local movements that perform in it. The ADV is calculated for each cell of the scenario in which it is spatially sampled obtaining a cue for different clustering methods. The ADV representation has been tested as the input of several classic classifiers and compared to other approaches using CAVIAR dataset sequences obtaining great accuracy in the recognition of the behaviour of people in a Shopping Centre.

Punishing Local Incumbents for the Local Economy

After decennia of research on economic voting, it is now established that the state of the economy affects voting behaviour. Nevertheless, this conclusion is the result of a focus on predominantly national-level economies and national-level elections. In this paper, we show that at a local level as well, mechanisms of accountability linked to the economy are at work. The local economic context affected voting behaviour in the 2012 Belgian municipal elections, with a stronger increase of unemployment rates in their municipality significantly decreasing the probability that voters choose an incumbent party. Additionally, we observe that voters are not opportunistically voting for incumbents who lower tax rates. Instead, voters seem to be holding local incumbents accountable for local economic conditions. We hence conclude that voters care about economic outcomes, not about what specific policies are implemented to reach these outcomes.

Behaviour of the energy gap in a model of Josephson coupled Bose-Einstein condensates

In this work we investigate the energy gap between the ground state and the first excited state in a model of two single-mode Bose-Einstein condensates coupled via Josephson tunnelling. The ene:rgy gap is never zero when the tunnelling interaction is non-zero. The gap exhibits no local minimum below a threshold coupling which separates a delocalized phase from a self-trapping phase that occurs in the absence of the external potential. Above this threshold point one minimum occurs close to the Josephson regime, and a set of minima and maxima appear in the Fock regime. Expressions for the position of these minima and maxima are obtained. The connection between these minima and maxima and the dynamics for the expectation value of the relative number of particles is analysed in detail. We find that the dynamics of the system changes as the coupling crosses these points.

Altitudinal variation in behavioural thermoregulation: Local adaptation vs. plasticity in California grasshoppers

We investigated the adaptive significance of behavioural thermoregulation in univoltine populations of the grasshopper Melanoplus sanguinipes along an altitudinal gradient in California using laboratory tests of animals raised under different temperatures. Trials consisted of continuous body temperature measurements with semi-implanted microprobes in a test arena, and observation and simultaneous recording of behavioural responses. These responses included mobility, basking and orientation of the body axes (aspect angle) towards a radiation source. Mobility and basking are determined by the altitudinal origin of the parental generation and not by the temperature treatments. With increasing altitude, individuals tend increasingly to raise body temperatures via mobility and increased basking. In contrast, body orientation towards the radiation source is influenced by the temperature treatments but not by the altitude of origin. Individuals experiencing higher temperatures during rearing show a lower tendency to lateral flanking. We conclude that body orientation responses are not adapted locally. In contrast other components of the behavioural syndrome that increase body temperature, such as mobility and basking, are adaptive in response to local selection pressure. The thermoregulatory syndrome of these grasshoppers is an important contribution to life-history adaptations that appropriately match season lengths.

Guiding local regression using visualisation

Solving many scientific problems requires effective regression and/or classification models for large high-dimensional datasets. Experts from these problem domains (e.g. biologists, chemists, financial analysts) have insights into the domain which can be helpful in developing powerful models but they need a modelling framework that helps them to use these insights. Data visualisation is an effective technique for presenting data and requiring feedback from the experts. A single global regression model can rarely capture the full behavioural variability of a huge multi-dimensional dataset. Instead, local regression models, each focused on a separate area of input space, often work better since the behaviour of different areas may vary. Classical local models such as Mixture of Experts segment the input space automatically, which is not always effective and it also lacks involvement of the domain experts to guide a meaningful segmentation of the input space. In this paper we addresses this issue by allowing domain experts to interactively segment the input space using data visualisation. The segmentation output obtained is then further used to develop effective local regression models.

Macro-level change and micro-level effects:a twenty year perspective on changing grocery shopping behaviour in Britain

In this paper we summarise key elements of retail change in Britain over a twenty-year period. The time period is that covered by a funded study into long-term change in grocery shopping habits in Portsmouth, England. The major empirical findings—to which we briefly allude—are reported elsewhere: the present task is to assess the wider context underlying that change. For example, it has frequently been stated that retailing in the UK is not as competitive as in other leading economies. As a result, the issue of consumer choice has become increasingly important politically. Concerns over concentration in the industry, new format development and market definition have been expressed by local planners, competition regulators and consumer groups. Macro level changes over time have also created market inequality in consumer opportunities at a local level—hence our decision to attempt a local-level study. Situational factors affecting consumer experiences over time at the local level involve the changing store choice sets available to particular consumers. Using actual consumer experiences thus becomes a yardstick for assessing the practical effectiveness of policy making. The paper demonstrates that choice at local level is driven by store use and that different levels of provision reflect real choice at the local level. Macro-level policy and ‘one size fits all’ approaches to regulation, it is argued, do not reflect the changing reality of grocery shopping. Accordingly, arguments for a more local and regional approach to regulation are made.

Collective behaviour in a square lattice of driven Duffing resonators coupled to van der Pol oscillators

The global and local synchronisation of a square lattice composed of alternating Duffing resonators and van der Pol oscillators coupled through displacement is studied. The lattice acts as a sensing device in which the input signal is characterised by an external driving force that is injected into the system through a subset of the Duffing resonators. The parameters of the system are taken from MEMS devices. The effects of the system parameters, the lattice architecture and size are discussed.

The influence of utilising government initiatives, servicing foreign MNCs and internationalisation on strategic planning process of local companies in Singapore

This research focuses on two groups of local companies; namely, high-growth local companies and other local companies, to examine and compare the influence of utilising governmental initiatives, servicing foreign MNCs and internationalisation on their strategic planning process. The theme of this thesis argues that the approach of an organisation towards strategic planning is not only determined by the internal influences; namely, its firm size and the planning behaviour and attitude of an entrepreneur, as revealed in the literature, but it can also be affected by external influences. The theoretical contribution of this research determines this unique situation in Singapore, and tests the robustness of the conventional models of planning in smaller companies. As a result of the external influences, this study reveals that local companies are more likely to undertake a much more formal strategic planning than the conventional Western literature and models would indicate. High-growth local companies, in comparison, however, had undertaken a more formal and rigorous strategic planning process than other local companies.

Guiding local regression using visualisation

Solving many scientific problems requires effective regression and/or classification models for large high-dimensional datasets. Experts from these problem domains (e.g. biologists, chemists, financial analysts) have insights into the domain which can be helpful in developing powerful models but they need a modelling framework that helps them to use these insights. Data visualisation is an effective technique for presenting data and requiring feedback from the experts. A single global regression model can rarely capture the full behavioural variability of a huge multi-dimensional dataset. Instead, local regression models, each focused on a separate area of input space, often work better since the behaviour of different areas may vary. Classical local models such as Mixture of Experts segment the input space automatically, which is not always effective and it also lacks involvement of the domain experts to guide a meaningful segmentation of the input space. In this paper we addresses this issue by allowing domain experts to interactively segment the input space using data visualisation. The segmentation output obtained is then further used to develop effective local regression models.

Modelling short crack growth behaviour in nickel-base superalloys

This paper provides a description of the features and mechanisms of facetted short crack growth in Ni-base superalloys, and briefly reviews existing short crack growth models in terms of their application to Ni-base alloys. The concept of “soft barriers” is introduced to produce a new two-phase model for local microstructural effects on short crack growth in Waspaloy. This is derived from detailed observations of crack growth through individual grains. The model differs from all previous approaches in highlighting the importance of crack path perturbations within grains. Potential applications of the model in alloy development are discussed.

Local Goals Driven Hierarchical Reinforcement Learning

* This research was partially supported by the Latvian Science Foundation under grant No.02-86d.

Cognitive behaviour therapy for mothers of children with food allergy:a case series

Background: Food allergy affects quality of life in patients and parents and mothers report high levels of anxiety and stress. Cognitive Behaviour Therapy (CBT) may be helpful in reducing the psychological impact of food allergy. The aim of this study was to examine the appropriateness and effectiveness of CBT to improve psychological outcomes in parents of children with food allergy. Methods: Five parents (all mothers) from a local allergy clinic requested to have CBT; six mothers acted as controls and completed questionnaires only. CBT was individual and face-to face and lasted 12 weeks. All participants completed measures of anxiety and depression, worry, stress, general mental health, generic and food allergy specific quality of life at baseline and at 12 weeks. Results: Anxiety, depression and worry in the CBT group significantly reduced and overall mental health and QoL significantly improved from baseline to 12 weeks (all p < 0.05) in mothers in the CBT group; control group scores remained stable. Conclusions: CBT appears to be appropriate and effective in mothers of children with food allergy and a larger randomised control trial now needs to be conducted. Ways in which aspects of CBT can be incorporated into allergy clinic visits need investigation.