A study of the Type II-P supernova 2003gd in M74

We present photometric and spectroscopic data of the Type II-P supernova (SN II-P) 2003gd, which was discovered in M74 close to the end of its plateau phase. SN 2003gd is the first Type II supernova ( SN) to have a directly confirmed red supergiant ( RSG) progenitor. We compare SN 2003gd to SN 1999 em, a similar SN II-P, and estimate an explosion date of 2003 March 18. We determine a reddening towards the SN of E(B-V) = 0.14 +/- 0.06, using three different methods. We also calculate three new distances to M74 of 9.6 +/- 2.8, 7.7 +/- 1.7 and 9.6 +/- 2.2 Mpc. The former was estimated using the standard candle method (SCM), for Type II supernovae (SNe II), and the latter two using the brightest supergiants method (BSM). When combined with existing kinematic and BSM distance estimates, we derive a mean value of 9.3 +/- 1.8 Mpc. SN 2003gd was found to have a lower tail luminosity compared with other normal Type II-P supernovae ( SNe II-P) bringing into question the nature of this SN. We present a discussion concluding that this is a normal SN II-P, which is consistent with the observed progenitor mass of 8(-2)(+4) M-circle dot.

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.

The Teaching Space Allocation Problem with splitting

A standard problem within universities is that of teaching space allocation which can be thought of as the assignment of rooms and times to various teaching activities. The focus is usually on courses that are expected to fit into one room. However, it can also happen that the course will need to be broken up, or ‘split’, into multiple sections. A lecture might be too large to fit into any one room. Another common example is that of seminars or tutorials. Although hundreds of students may be enrolled on a course, it is often subdivided into particular types and sizes of events dependent on the pedagogic requirements of that particular course. Typically, decisions as to how to split courses need to be made within the context of limited space requirements. Institutions do not have an unlimited number of teaching rooms, and need to effectively use those that they do have. The efficiency of space usage is usually measured by the overall ‘utilisation’ which is basically the fraction of the available seat-hours that are actually used. A multi-objective optimisation problem naturally arises; with a trade-off between satisfying preferences on splitting, a desire to increase utilisation, and also to satisfy other constraints such as those based on event location and timetabling conflicts. In this paper, we explore such trade-offs. The explorations themselves are based on a local search method that attempts to optimise the space utilisation by means of a ‘dynamic splitting’ strategy. The local moves are designed to improve utilisation and satisfy the other constraints, but are also allowed to split, and un-split, courses so as to simultaneously meet the splitting objectives.

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.

Bcl-2 expression in sequential biopsies of potentially malignant oral mucosal lesions assessed by immunocytochemistry

OBJECTIVE: To examine, for the first time Bcl-2 expression in sequential (autogenous) oral mucosal biopsies taken from the same sites in a gender, risk-factor matched, Caucasoid sample, over a 21-year period,

Modification of smooth muscle Ca2+-sparks by tetracaine: evidence for sequential RyR activation.

Spontaneous Ca(2+)-sparks were imaged using confocal line scans of fluo-4 loaded myocytes in retinal arterioles. Tetracaine produced concentration-dependent decreases in spark frequency, and modified the spatiotemporal characteristics of residual sparks. Tetracaine (10 microM) reduced the rate of rise but prolonged the average rise time so that average spark amplitude was unaltered. The mean half-time of spark decay was also unaffected, suggesting that spark termination, although delayed, remained well synchronized. Sparks spread transversely across the myocytes in these vessels, and the speed of spread within individual sparks was slowed by approximately 60% in 10 microM tetracaine, as expected if the spark was propagated across the cell but the average P(o) for RyRs was reduced. Staining of isolated vessels with BODIPY-ryanodine and di-4-ANEPPS showed that RyRs were located both peripherally, adjacent to the plasma membrane, and in transverse extensions of the SR from one side of the cell to the other. Immuno-labelling of retinal flat mounts demonstrated the presence RyR(2) in arteriole smooth muscle but not RyR(1). We conclude that Ca(2+)-sparks in smooth muscle can result from sequential activation of RyRs distributed over an area of several microm(2), rather than from tightly clustered channels as in striated muscle.

Prediction- and simulation-error based perceptron training: Solution space analysis and a novel combined training scheme

Previous papers have noted the difficulty in obtaining neural models which are stable under simulation when trained using prediction-error-based methods. Here the differences between series-parallel and parallel identification structures for training neural models are investigated. The effect of the error surface shape on training convergence and simulation performance is analysed using a standard algorithm operating in both training modes. A combined series-parallel/parallel training scheme is proposed, aiming to provide a more effective means of obtaining accurate neural simulation models. Simulation examples show the combined scheme is advantageous in circumstances where the solution space is known or suspected to be complex. (c) 2006 Elsevier B.V. All rights reserved.

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.