A matrix iteration for dynamic network summaries

We propose a new algorithm for summarizing properties of large-scale time-evolving networks. This type of data, recording connections that come and go over time, is being generated in many modern applications, including telecommunications and on-line human social behavior. The algorithm computes a dynamic measure of how well pairs of nodes can communicate by taking account of routes through the network that respect the arrow of time. We take the conventional approach of downweighting for length (messages become corrupted as they are passed along) and add the novel feature of downweighting for age (messages go out of date). This allows us to generalize widely used Katz-style centrality measures that have proved popular in network science to the case of dynamic networks sampled at non-uniform points in time. We illustrate the new approach on synthetic and real data.

Dynamic capabilities in a sixth generation family firm: entrepreneurship and the Bibby Line

In this paper we draw on the theory of dynamic capabilities to examine development of the only surviving family-owned Liverpool shipping company. The Bibby Line was founded in 1807 to take advantage of the growing sea-trade based in Liverpool. The company remained in shipping until the mid-1960s, when a series of external crises led the owner, Derek Bibby, to begin a process of diversification. In the last 50 years, the Bibby Line has grown into a £1bn business with interests in retail, distribution and financial services as well as a continuing commitment to shipping. Our intention is to demonstrate how multigenerational ownership contributes to the creation of dynamic capabilities in family firms. The distinctive nature of Bibby as a long-standing family business is related to unique assets such as patient capital, flexible governance structures as well as the ability to mobilise social and human capital.

Steady state and dynamic modelling of nitrogen in the River Kennet: impacts of land use change since the 1930s

Steady state and dynamic models have been developed and applied to the River Kennet system. Annual nitrogen exports from the land surface to the river have been estimated based on land use from the 1930s and the 1990s. Long term modelled trends indicate that there has been a large increase in nitrogen transport into the river system driven by increased fertiliser application associated with increased cereal production, increased population and increased livestock levels. The dynamic model INCA Integrated Nitrogen in Catchments. has been applied to simulate the day-to-day transport of N from the terrestrial ecosystem to the riverine environment. This process-based model generates spatial and temporal data and reproduces the observed instream concentrations. Applying the model to current land use and 1930s land use indicates that there has been a major shift in the short term dynamics since the 1930s, with increased river and groundwater concentrations caused by both non-point source pollution from agriculture and point source discharges. �

Influence of geographical origin, host animal and stx gene on the virulence characteristics of Escherichia coli O26 strains

The influence of geographical origin, host animal and presence of the stx gene on the virulence of Escherichia coli O26 strains from ruminants was determined in this study. A clear association was found between the virulence profile and geographical origin of Shiga-toxigenic E. coli (STEC) O26 strains, with UK STEC O26 strains harbouring virtually identical profiles, whilst central European strains showed considerable heterogeneity in plasmid-encoded genes. The former group were also more likely to be non-motile and katP gene positive. Comparison of UK STEC and atypical enteropathogenic E. coli (aEPEC O26 strains showed that the presence of the stx1 gene was positively correlated with the presence of espP and katP genes and negatively associated with the presence of the yagP-yagT region and with rhamnose fermentation. In contrast to the uniform profiles of STEC O26 strains from ruminants in the UK, aEPEC O26 strains of bovine and ovine origin showed diverse profiles both within and between groups, and could not be separated into discrete groups. These results indicate that the characteristics of UK O26 strains from ruminants are distinct from those of O26 strains from ruminants and humans in other regions in central Europe. Such differences are expected to influence the zoonotic potential of this pathogen and the subsequent incidence of O26-associated human disease.

CLSM method for the dynamic observation of pH change within polymer matrices for oral delivery

If acid-sensitive drugs or cells are administered orally, there is often a reduction in efficacy associated with gastric passage. Formulation into a polymer matrix is a potential method to improve their stability. The visualization of pH within these materials may help better understand the action of these polymer systems and allow comparison of different formulations. We herein describe the development of a novel confocal laser-scanning microscopy (CLSM) method for visualizing pH changes within polymer matrices and demonstrate its applicability to an enteric formulation based on chitosan-coated alginate gels. The system in question is first shown to protect an acid-sensitive bacterial strain to low pH, before being studied by our technique. Prior to this study, it has been claimed that protection by these materials is a result of buffering, but this has not been demonstrated. The visualization of pH within these matrices during exposure to a pH 2.0 simulated gastric solution showed an encroachment of acid from the periphery of the capsule, and a persistence of pHs above 2.0 within the matrix. This implies that the protective effect of the alginate-chitosan matrices is most likely due to a combination of buffering of acid as it enters the polymer matrix and the slowing of acid penetration.

Will greenhouse gas-induced warming over the next 50 years lead to higher frequency and greater intensity of hurricanes?

The use of a high resolution atmospheric model at T106 resolution, for studying the influence of greenhouse warming on tropical storm climatology, is investigated. The same method for identifying the storms has been used as in a previous study by Bengtsson et al. The sea surface temperature anomalies have been taken from a previous transient climate change experiment, obtained with a low resolution ocean-atmosphere coupled model. The global distribution of the storms, at the time when the CO2 concentration in the atmosphere had doubled, agrees in geographical position and seasonal variability with that of the present climate, but the number of storms is significantly reduced, particularly at the Southern Hemisphere. The main reason to this, appear to be connected to changes in the large scale circulation, such as a weaker Hadley circulation and stronger upper air westerlies. The low level vorticity in the hurricane genesis regions is generally reduced compared to the present climate, while the vertical tropospheric wind shear is somewhat increased. Most tropical storm regions indicate reduced surface windspeeds and a slightly weaker hydrological cycle.

Hurricane-type vortices in a general circulation model

A very high resolution atmospheric general circulation model, T106-L19, has been used for the simulation of hurricanes in a multi-year numerical experiment. Individual storms as well as their geographical and seasonal distribution agree remarkably well with observations. In spite of the fact that only the thermal and dynamical structure of the storms have been used as criteria of their identification, practically all of them occur in areas where the sea surface temperature is higher or equal to 26 °C. There are considerable variations from year to year in the number of storms in spite of the fact that there are no interannual variations in the SST pattern. It is found that the number of storms in particular areas appear to depend on the intensity of the Hadley-Walker cell. The result is clearly resolution-dependant. At lower horizonal resolution, T42, for example, the intensity of the storms is significantly reduced and their overall structure is less realistic, including their vertical form and extent.

Centrality and spectral radius in dynamic communication networks

We explore the influence of the choice of attenuation factor on Katz centrality indices for evolving communication networks. For given snapshots of a network observed over a period of time, recently developed communicability indices aim to identify best broadcasters and listeners in the network. In this article, we looked into the sensitivity of communicability indices on the attenuation factor constraint, in relation to spectral radius (the largest eigenvalue) of the network at any point in time and its computation in the case of large networks. We proposed relaxed communicability measures where the spectral radius bound on attenuation factor is relaxed and the adjacency matrix is normalised in order to maintain the convergence of the measure. Using a vitality based measure of both standard and relaxed communicability indices we looked at the ways of establishing the most important individuals for broadcasting and receiving of messages related to community bridging roles. We illustrated our findings with two examples of real-life networks, MIT reality mining data set of daily communications between 106 individuals during one year and UK Twitter mentions network, direct messages on Twitter between 12.4k individuals during one week.

Dynamic agility of inter-organizational processes

The agility of inter-organizational process represents the ability of virtual enterprise to respond rapidly to the changing market environment. Many theories and methodologies about inter-organizational process have been developed but the dynamic agility has seldom been addressed. A virtual enterprise whose process has a high dynamic agility will be able to adjust with the changing environment in short time and low cost. This paper analyzes the agility of inter-organizational process from a dynamic perspective. Two indexes are proposed to evaluate the dynamic agility: time and cost. Furthermore, the method to measure the dynamic agility using simulation is studied. Finally, a case study is given to illustrate the method to measure the dynamic agility.

A dynamic model of neurovascular coupling: Implications for blood vessel dilation and constriction

Neurovascular coupling in response to stimulation of the rat barrel cortex was investigated using concurrent multichannel electrophysiology and laser Doppler flowmetry. The data were used to build a linear dynamic model relating neural activity to blood flow. Local field potential time series were subject to current source density analysis, and the time series of a layer IV sink of the barrel cortex was used as the input to the model. The model output was the time series of the changes in regional cerebral blood flow (CBF). We show that this model can provide excellent fit of the CBF responses for stimulus durations of up to 16 s. The structure of the model consisted of two coupled components representing vascular dilation and constriction. The complex temporal characteristics of the CBF time series were reproduced by the relatively simple balance of these two components. We show that the impulse response obtained under the 16-s duration stimulation condition generalised to provide a good prediction to the data from the shorter duration stimulation conditions. Furthermore, by optimising three out of the total of nine model parameters, the variability in the data can be well accounted for over a wide range of stimulus conditions. By establishing linearity, classic system analysis methods can be used to generate and explore a range of equivalent model structures (e.g., feed-forward or feedback) to guide the experimental investigation of the control of vascular dilation and constriction following stimulation.

A dynamic causal model of the coupling between pulse stimulation and neural activity

We present a dynamic causal model that can explain context-dependent changes in neural responses, in the rat barrel cortex, to an electrical whisker stimulation at different frequencies. Neural responses were measured in terms of local field potentials. These were converted into current source density (CSD) data, and the time series of the CSD sink was extracted to provide a time series response train. The model structure consists of three layers (approximating the responses from the brain stem to the thalamus and then the barrel cortex), and the latter two layers contain nonlinearly coupled modules of linear second-order dynamic systems. The interaction of these modules forms a nonlinear regulatory system that determines the temporal structure of the neural response amplitude for the thalamic and cortical layers. The model is based on the measured population dynamics of neurons rather than the dynamics of a single neuron and was evaluated against CSD data from experiments with varying stimulation frequency (1–40 Hz), random pulse trains, and awake and anesthetized animals. The model parameters obtained by optimization for different physiological conditions (anesthetized or awake) were significantly different. Following Friston, Mechelli, Turner, and Price (2000), this work is part of a formal mathematical system currently being developed (Zheng et al., 2005) that links stimulation to the blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal through neural activity and hemodynamic variables. The importance of the model described here is that it can be used to invert the hemodynamic measurements of changes in blood flow to estimate the underlying neural activity.