Models of open populations with space-limited recruitment: extension of theory and application to the barnacle Chthamalus montagui.

1. Barnacles are a good model organism for the study of open populations with space-limited recruitment. These models are applicable to other species with open supply of new individuals and resource limitation. The inclusion of space in models leads to reductions in recruitment with increasing density, and thus predictions of population size and stability are possible. 2. Despite the potential generality of a demographic theory for open space-limited populations, the models currently have a narrow empirical base. In this study, a model for an open population with space-limited recruitment was extended to include size-specific survival and promotions to any size class. The assumptions of this model were tested using data from a pan-European study of the barnacle Chthamalus montagui Southward. Two models were constructed: a 6-month model and a periodic annual model. Predicted equilibria and their stabilities were compared between shores. 3. Tests of model assumptions supported the extension of the theory to include promotions to any size class. Mortality was found to be size-specific and density independent. Studied populations were open, with recruitment proportional to free space. 4. The 6-month model showed a significant interaction between time and location for equilibrium free space. This may have been due to contrasts in the timing of structuring processes (i.e. creating and filling space) between Mediterranean and Atlantic systems. Integration of the 6-month models into a periodic annual model removed the differences in equilibrium-free space between locations. 5. Model predictions show a remarkable similarity between shores at a European scale. Populations were persistent and all solutions were stable. This reflects the apparent absence of density-dependent mortality and a high adult survivorship in C. montagui. As populations are intrinsically stable, observations of fluctuations in density are directly attributable to variations in the environmental forcing of recruitment or mortality

WASP-1b and WASP-2b: Two new transiting exoplanets detected with SuperWASP and SOPHIE

We have detected low-amplitude radial-velocity variations in two stars, USNO-B1.0 1219-0005465 (GSC 02265-00107 = WASP-1) and USNO-B1.0 0964-0543604 (GSC 00522-01199 = WASP-2). Both stars were identified as being likely host stars of transiting exoplanets in the 2004 SuperWASP wide-field transit survey. Using the newly commissioned radial-velocity spectrograph SOPHIE at the Observatoire de Haute-Provence, we found that both objects exhibit reflex orbital radial-velocity variations with amplitudes characteristic of planetary-mass companions and in-phase with the photometric orbits. Line-bisector studies rule out faint blended binaries as the cause of either the radial-velocity variations or the transits. We perform preliminary spectral analyses of the host stars, which together with their radial-velocity variations and fits to the transit light curves yield estimates of the planetary masses and radii. WASP-1b and WASP-2b have orbital periods of 2.52 and 2.15 d, respectively. Given mass estimates for their F7V and K1V primaries, we derive planet masses 0.80-0.98 and 0.81-0.95 times that of Jupiter, respectively. WASP-1b appears to have an inflated radius of at least 1.33 RJup, whereas WASP-2b has a radius in the range 0.65-1.26 RJup.

A new look at the pulsating DB white dwarf GD 358: Line-of-sight velocity measurements and constraints on model atmospheres

We report on our findings of the bright, pulsating, helium atmosphere white dwarf GD 358, based on time-resolved optical spectrophotometry. We identify 5 real pulsation modes and at least 6 combination modes at frequencies consistent with those found in previous observations. The measured Doppler shifts from our spectra show variations with amplitudes of up to 5.5 km s-1 at the frequencies inferred from the flux variations. We conclude that these are variations in the line-of-sight velocities associated with the pulsational motion. We use the observed flux and velocity amplitudes and phases to test theoretical predictions within the convective driving framework, and compare these with similar observations of the hydrogen atmosphere white dwarf pulsators (DAVs). The wavelength dependence of the fractional pulsation amplitudes (chromatic amplitudes) allows us to conclude that all five real modes share the same spherical degree, most likely, l=1. This is consistent with previous identifications based solely on photometry. We find that a high signal-to-noise mean spectrum on its own is not enough to determine the atmospheric parameters and that there are small but significant discrepancies between the observations and model atmospheres. The source of these remains to be identified. While we infer Teff =24 kK and log g ~ 8.0 from the mean spectrum, the chromatic amplitudes, which are a measure of the derivative of the flux with respect to the temperature, unambiguously favour a higher effective temperature, 27 kK, which is more in line with independent determinations from ultra-violet spectra.

Towards Improving the Utilisation of University Teaching Space

There is a perception that teaching space in universities is a rather scarce resource. However, some studies have revealed that in many institutions it is actually chronically under-used. Often, rooms are occupied only half the time, and even when in use they are often only half full. This is usually measured by the ‘utilization’ which is defined as the percentage of available ‘seat-hours’ that are employed. Within real institutions, studies have shown that this utilization can often take values as low as 20–40%. One consequence of such a low level of utilization is that space managers are under pressure to make more efficient use of the available teaching space. However, better management is hampered because there does not appear to be a good understanding within space management (near-term planning) of why this happens. This is accompanied, within space planning (long-term planning) by a lack of experise on how best to accommodate the expected low utilizations. This motivates our two main goals: (i) To understand the factors that drive down utilizations, (ii) To set up methods to provide better space planning. Here, we provide quantitative evidence that constraints arising from timetabling and location requirements easily have the potential to explain the low utilizations seen in reality. Furthermore, on considering the decision question ‘Can this given set of courses all be allocated in the available teaching space?’ we find that the answer depends on the associated utilization in a way that exhibits threshold behaviour: There is a sharp division between regions in which the answer is ‘almost always yes’ and those of ‘almost always no’. Through analysis and understanding of the space of potential solutions, our work suggests that better use of space within universities will come about through an understanding of the effects of timetabling constraints and when it is statistically likely that it will be possible for a set of courses to be allocated to a particular space. The results presented here provide a firm foundation for university managers to take decisions on how space should be managed and planned for more effectively. Our multi-criteria approach and new methodology together provide new insight into the interaction between the course timetabling problem and the crucial issue of space planning.

Packet classification by multi-level cutting of the classification space: An algorithmic-architectural solution for IP packet classification in next generation networks

Traditionally, the Internet provides only a “best-effort” service, treating all packets going to the same destination equally. However, providing differentiated services for different users based on their quality requirements is increasingly becoming a demanding issue. For this, routers need to have the capability to distinguish and isolate traffic belonging to different flows. This ability to determine the flow each packet belongs to is called packet classification. Technology vendors are reluctant to support algorithmic solutions for classification due to their non-deterministic performance. Although CAMs are favoured by technology vendors due to their deterministic high lookup rates, they suffer from the problems of high power dissipation and high silicon cost. This paper provides a new algorithmic-architectural solution for packet classification that mixes CAMs with algorithms based on multi-level cutting the classification space into smaller spaces. The provided solution utilizes the geometrical distribution of rules in the classification space. It provides the deterministic performance of CAMs, support for dynamic updates, and added flexibility for system designers.

Exploring Technology Related Design-Space Limitations of High Performance Network Processing

This paper summarizes numerous research activities in high-performance networks and network security processing, and explores technology related performance constraints such as critical performance limitations of circuit architectures, which are set by the semiconductor technologies.

Tracking biological invasions in space and time: elucidating the invasive history of the green alga Codium fragile using old DNA

With the advent of 'ancient DNA' studies on preserved material of extant and extinct species, museums and herbaria now represent an important although still underutilized resource in molecular ecology. The ability to obtain sequence data from archived specimens can reveal the recent history of cryptic species and introductions. We have analysed extant and herbarium samples of the highly invasive green alga Codium fragile, many over 100 years old, to identify cryptic accessions of the invasive strain known as C. fragile ssp. tomentosoides, which can be identified by a unique haplotype. Molecular characterization of specimens previously identified as native in various regions shows that the invasive tomentosoides strain has been colonizing new habitats across the world for longer than records indicate, in some cases nearly 100 years before it was noticed. It can now be found in the ranges of all the other native haplotypes detected, several of which correspond to recognized subspecies. Within regions in the southern hemisphere there was a greater diversity of haplotypes than in the northern hemisphere, probably as a result of dispersal by the Antarctic Circumpolar Current. The findings of this study highlight the importance of herbaria in preserving contemporaneous records of invasions as they occur, especially when invasive taxa are cryptic.

A New Theory for Perpendicular Transport of Cosmic Rays

We present an improved nonlinear theory for the perpendicular transport of charged particles. This approach is based on an improved nonlinear treatment of field-line random walk in combination with a generalized compound diffusion model. The generalized compound diffusion model employed is more systematic and reliable, in comparison with previous theories. Furthermore, the theory shows remarkably good agreement with test-particle simulations and solar wind observations.

Monotonically normal topological vector spaces are stratifiable

We prove that for any Hausdorff topological vector space E over the field R there exists A subset of E such that E is homeomorphic to a subset of A x R and A x R is homeomorphic to a subset of E. Using this fact we prove that E is monotonically normal if and only if E is stratifiable.

A new Jacobian matrix for optimal learning of single-layer neural networks

This paper investigates the learning of a wide class of single-hidden-layer feedforward neural networks (SLFNs) with two sets of adjustable parameters, i.e., the nonlinear parameters in the hidden nodes and the linear output weights. The main objective is to both speed up the convergence of second-order learning algorithms such as Levenberg-Marquardt (LM), as well as to improve the network performance. This is achieved here by reducing the dimension of the solution space and by introducing a new Jacobian matrix. Unlike conventional supervised learning methods which optimize these two sets of parameters simultaneously, the linear output weights are first converted into dependent parameters, thereby removing the need for their explicit computation. Consequently, the neural network (NN) learning is performed over a solution space of reduced dimension. A new Jacobian matrix is then proposed for use with the popular second-order learning methods in order to achieve a more accurate approximation of the cost function. The efficacy of the proposed method is shown through an analysis of the computational complexity and by presenting simulation results from four different examples.

Hull fouling on commercial ships as a vector of macroalgal introduction

Hull fouling is thought to have been the vector of introduction for many algal species. We studied ships arriving at a Mediterranean harbour to clarify the present role of commercial cargo shipping in algal introductions. A total of 31 macroalgal taxa were identified from 22 sampled hulls. The majority of records (58%) were of species with a known cosmopolitan geographical distribution. Due to a prevalence of cosmopolitan species and a high turnover of fouling communities, species composition of assemblages did not appear to be influenced by the area of origin, length of ship or age of coating. In the light of the present results, hull fouling on standard trading commercial vessels does not seem to pose a significant risk for new macroalgal species introductions. However, a high proportion of non-cosmopolitan species found on a ship with non-toxic coating may modify this assessment, especially in the light of the increasing use of such coatings and the potential future changes in shipping routes.

Surrogate-Based Optimization Using Multifidelity Models with Variable Parameterization and Corrected Space Mapping

Surrogate-based-optimization methods provide a means to achieve high-fidelity design optimization at reduced computational cost by using a high-fidelity model in combination with lower-fidelity models that are less expensive to evaluate. This paper presents a provably convergent trust-region model-management methodology for variableparameterization design models: that is, models for which the design parameters are defined over different spaces. Corrected space mapping is introduced as a method to map between the variable-parameterization design spaces. It is then used with a sequential-quadratic-programming-like trust-region method for two aerospace-related design optimization problems. Results for a wing design problem and a flapping-flight problem show that the method outperforms direct optimization in the high-fidelity space. On the wing design problem, the new method achieves 76% savings in high-fidelity function calls. On a bat-flight design problem, it achieves approximately 45% time savings, although it converges to a different local minimum than did the benchmark.